Abstract


The purpose of this paper is to present a differential equation with delay from biological excitable medium. Existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results for the solution of the Cauchy problem of biological excitable medium are obtained using weakly Picard operator theory.

Authors

Diana Otrocol
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy

Keywords

excitable medium; differential-delay equations; weakly Picard operator.

Paper coordinates

D. Otrocol, A differential equation with delay from biology, J. Appl. Math. & Informatics, 26 (2008) nos. 5-6, pp. 1037–1048.

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 J. Appl. Math. & Informatics

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JAMI

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2234-8417.

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2234-8417

 

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[1] J. K. Hale, Introduction to functional differential equations, Springer-Verlag, 1993.
[2] B. N. Hidirov, Regulation mechanism of living system, J. Scientiae Mathematicae Japonicae 64(2006), No.2, 497-504.
[3] M. B. Hidirova, Dynamics of biological excitable medium, J. Scientiae Mathematicae Japonicae 64(2006), No.2, 755-763.
[4] V. Mure¸san, Functional-Integral Equations, Mediamira, Cluj-Napoca, 2003.
[5] D. Otrocol, Data dependence for the solution of a Lotka-Volterra system with two delays, Mathematica 48(2006), No.71, 61-68.
[6] D. Otrocol, Lotka-Volterra system with two delays via weakly Picard operators, Nonlinear Analysis Forum 10(2005), No.2, 193-199.
[7] I. A. Rus, Picard operators and applications, J. Scientiae Mathematicae Japonicae 58(2003), No.1, 191-219.
[8] I. A. Rus, Generalized Contractions and Applications, Cluj University Press, 2001.
[9] I. A. Rus, Weakly Picard operators and applications, Seminar of Fixed Point Theory, ClujNapoca, 2(2001), 41-58.
[10] M. Saidalieva, Modelling of regulation mechanism of cellular communities, J. Scientiae Mathematicae Japonicae 8(2003), 463-469.
[11] M. A. S¸erban, Fiber φ-contractions, Studia Univ. ”Babe¸s-Bolyai”, Mathematica 44(1999), No.3 , 99-108.

Paper (preprint) in HTML form

A DIFFERENTIAL EQUATION WITH DELAY FROM BIOLOGY

DIANA OTROCOL
Abstract

The purpose of this paper is to present a differential equation with delay from biological excitable medium. Existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results for the solution of the Cauchy problem of biological excitable medium are obtained using weakly Picard operator theory.

AMS Mathematics Subject Classification : 47H10, 47N20.
Key words and phrases : excitable medium, differential-delay equations, weakly Picard operator.

1. Introduction

In recent years the theory of excitable medium has rapidly developed and its results have been applied in various areas: chemistry, biology, ecology, electric engineering, populations dynamics, cardiology, neurology. At present, different approaches for the mathematical description of biological excitable medium by means of partial-differential equation, functional-differential, functional and discrete equations are applied. The papers [2], [3], [10] has offered the opportunity for understanding the normal regulation of living systems as well as its anomalies.

The activity of the ii-th element of the excitable medium can be described by the following equation:

xi(t)=aifi(x1(th),,xm(th))bixi(t)x_{i}^{\prime}(t)=a_{i}f_{i}\left(x_{1}(t-h),\ldots,x_{m}(t-h)\right)-b_{i}x_{i}(t) (1)

where xi(t)x_{i}(t) is the activity of the ii-th element; aia_{i} is the functional parameter of the ii-th element; fi()f_{i}(\cdot) is the feedback function; bib_{i} is the decay constant, i=1,m¯i=\overline{1,m}.

The aim of this paper is to study the following problem

xi(t)=aifi(x1(th),,xm(th))bixi(t)x_{i}^{\prime}(t)=a_{i}f_{i}\left(x_{1}(t-h),\ldots,x_{m}(t-h)\right)-b_{i}x_{i}(t) (2)

t[t0,b],i=1,m¯t\in\left[t_{0},b\right],i=\overline{1,m}, with initial conditions

xi(t)=φi(t),t[t0h,t0]x_{i}(t)=\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right] (3)

where
(H1)t0<b,h>0,t0,b,hR;\left(\mathrm{H}_{1}\right)t_{0}<b,h>0,t_{0},b,h\in R;
(H2)fiC(Rm,R),i=1,m¯\left(\mathrm{H}_{2}\right)f_{i}\in C\left(R^{m},R\right),i=\overline{1,m};
(H3)φiC([t0h,t0],R),i=1,m¯;\left(\mathrm{H}_{3}\right)\varphi_{i}\in C\left(\left[t_{0}-h,t_{0}\right],R\right),i=\overline{1,m};
(H4)\left(\mathrm{H}_{4}\right) there exists Lf>0L_{f}>0, such as:

|fi(u1,,um)fi(v1,,vm)|Lfi=1m|uivi|,\left|f_{i}\left(u_{1},\ldots,u_{m}\right)-f_{i}\left(v_{1},\ldots,v_{m}\right)\right|\leq L_{f}\sum_{i=1}^{m}\left|u_{i}-v_{i}\right|,

for all ui,viR,i=1,m¯u_{i},v_{i}\in R,i=\overline{1,m}.
By a solution of the problem (2)-(3) we understand the function x=(x1,,xm)Rmx=\left(x_{1},\ldots,x_{m}\right)\in R^{m} with xiC([t0h,b],R)C1([t0,b],R),i=1,m¯x_{i}\in C\left(\left[t_{0}-h,b\right],R\right)\cap C^{1}\left(\left[t_{0},b\right],R\right),i=\overline{1,m} which satisfies (2)-(3).

The problem (2)-(3) is equivalent with the following fixed point system:

xi(t)={φi(t),t[t0h,t0]φi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b]x_{i}(t)=\left\{\begin{array}[]{l}\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ \varphi_{i}\left(t_{0}\right)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}\left(x_{1}(s-h),\ldots,\right.\\ \left.\quad x_{m}(s-h)\right)ds,t\in\left[t_{0},b\right]\end{array}\right.

where xiC([t0h,b],R),i=1,m¯x_{i}\in C\left(\left[t_{0}-h,b\right],R\right),i=\overline{1,m}.
On the other hand, the system (2) is equivalent with

xi(t)={xi(t),t[t0h,t0]xi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b]x_{i}(t)=\left\{\begin{array}[]{l}x_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ x_{i}\left(t_{0}\right)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}\left(x_{1}(s-h),\ldots,\right.\\ \left.\quad x_{m}(s-h)\right)ds,t\in\left[t_{0},b\right]\end{array}\right.

where xiC([t0h,b],R),i=1,m¯x_{i}\in C\left(\left[t_{0}-h,b\right],R\right),i=\overline{1,m}.
In this paper we apply the weakly Picard operators technique to study the systems (4) and (5).

2. Weakly Picard operators

I.A. Rus introduced the Picard operators class (PO)(\mathrm{PO}) and the weakly Picard operators class (WPO) for the operators defined on a metric space and he gave basic notations, definitions and results in this field in many papers [7]-[9]. Some problems concerning this techniques were study in [4], [11], [5], [6].

Let ( X,dX,d ) be a metric space and A:XXA:X\rightarrow X an operator. We shall use the following notations:
FA:={xXA(x)=x}F_{A}:=\{x\in X\mid A(x)=x\} - the fixed point set of AA;
I(A):={YXA(Y)Y,Y}I(A):=\{Y\subset X\mid A(Y)\subset Y,Y\neq\emptyset\} - the family of the nonempty invariant subset of AA;
An+1:=AAn,A0=1X,A1=A,nN;A^{n+1}:=A\circ A^{n},A^{0}=1_{X},A^{1}=A,n\in N;
P(X):={YXY}P(X):=\{Y\subset X\mid Y\neq\emptyset\} - the set of the parts of XX;
H(Y,Z):=max{supyYinfzZd(y,z),supzZinfyYd(y,z)}H(Y,Z):=\max\left\{\sup_{y\in Y}\inf_{z\in Z}d(y,z),\sup_{z\in Z}\inf_{y\in Y}d(y,z)\right\}-the Pompeiu-Housdorff functional on P(X)×P(X)P(X)\times P(X).

Definition 1. ([7], [9]) Let ( X,dX,d ) be a metric space. An operator A:XXA:X\rightarrow X is a Picard operator (PO)(PO) if there exists xXx^{*}\in X such that:
(i) FA={x}F_{A}=\left\{x^{*}\right\};
(ii) the sequence (An(x0))nN\left(A^{n}\left(x_{0}\right)\right)_{n\in N} converges to xx^{*} for all x0Xx_{0}\in X.

Remark 1. ([7], [9]) Accordingly to the definition, the contraction principle insures that, if A:XXA:X\rightarrow X is an α\alpha-contraction on the complete metric space XX, then it is a Picard operator.

Theorem 1. ([7], [9]) (Data dependence theorem). Let ( X,dX,d ) be a complete metric space and A,B:XXA,B:X\rightarrow X two operators. We suppose that
(i) the operator AA is a α\alpha-contraction;
(ii) FBF_{B}\neq\emptyset;
(iii) there exists η>0\eta>0 such that

d(A(x),B(x))η,xX.d(A(x),B(x))\leq\eta,\forall x\in X.

Then, if FA={xA}F_{A}=\left\{x_{A}^{*}\right\} and xBFBx_{B}^{*}\in F_{B}, we have

d(xA,xB)η1αd\left(x_{A}^{*},x_{B}^{*}\right)\leq\frac{\eta}{1-\alpha}

Definition 2. ([7], [9]) Let ( X,dX,d ) be a metric space. An operator A:XXA:X\rightarrow X is a weakly Picard operator (WPO) if the sequence (An(x))nN\left(A^{n}(x)\right)_{n\in N} converges for all xXx\in X, and its limit (which may depend on xx ) is a fixed point of AA.

Theorem 2. ([7], [9]) Let (X,d)(X,d) be a metric space and A:XXA:X\rightarrow X an operator. The operator AA is weakly Picard operator if and only if there exists a partition of XX,

X=λΛXλX=\underset{\lambda\in\Lambda}{\cup}X_{\lambda}

where Λ\Lambda is the indices set of partition, such that:
(a) XλI(A),λΛX_{\lambda}\in I(A),\lambda\in\Lambda;
(b) A|Xλ:XλXλ\left.A\right|_{X_{\lambda}}:X_{\lambda}\rightarrow X_{\lambda} is a Picard operator for all λΛ\lambda\in\Lambda.

Definition 3. ([7], [9]) If AA is weakly Picard operator then we consider the operator AA^{\infty} defined by

A:XX,A(x):=limnAn(x)A^{\infty}:X\rightarrow X,A^{\infty}(x):=\lim_{n\rightarrow\infty}A^{n}(x)

It is clear that A(X)=FAA^{\infty}(X)=F_{A}.

Definition 4. ([7], [9]) Let AA be a weakly Picard operator and c>0c>0. The operator AA is cc-weakly Picard operator if

d(x,A(x))cd(x,A(x)),xXd\left(x,A^{\infty}(x)\right)\leq cd(x,A(x)),\forall x\in X

Example 1. ([7], [9]) Let (X,d)(X,d) be a complete metric space and A:XXA:X\rightarrow X a continuous operator. We suppose that there exists α[0,1)\alpha\in[0,1) such that

d(A2(x),A(x))α(x,A(x)),xXd\left(A^{2}(x),A(x)\right)\leq\alpha(x,A(x)),\forall x\in X

Then AA is cc-weakly Picard operator with c=11αc=\frac{1}{1-\alpha}.

Theorem 3. ([7], [9]) Let ( X,dX,d ) be a metric space and Ai:XX,i=1,2A_{i}:X\rightarrow X,i=1,2. Suppose that
(i) the operator AiA_{i} is cic_{i}-weakly Picard operator, i=1,2i=1,2;
(ii) there exists η>0\eta>0 such that

d(A1(x),A2(x))η,xXd\left(A_{1}(x),A_{2}(x)\right)\leq\eta,\forall x\in X

Then H(FA1,FA2)ηmax(c1,c2)H\left(F_{A_{1}},F_{A_{2}}\right)\leq\eta\max\left(c_{1},c_{2}\right).

Theorem 4. ([7], [9]) (Fibre contraction principle). Let ( X,dX,d ) and ( Y,ρY,\rho ) be two metric spaces and A:X×YX×Y,A=(B,C),(B:XX,C:X×YY)A:X\times Y\rightarrow X\times Y,A=(B,C),(B:X\rightarrow X,C:X\times Y\rightarrow Y) a triangular operator. We suppose that
(i) (Y,ρ)(Y,\rho) is a complete metric space;
(ii) the operator BB is Picard operator;
(iii) there exists l[0,1)l\in[0,1) such that C(x,):YYC(x,\cdot):Y\rightarrow Y is a ll-contraction, for all xXx\in X;
(iv) if (x,y)FA\left(x^{*},y^{*}\right)\in F_{A}, then C(,y)C\left(\cdot,y^{*}\right) is continuous in xx^{*}.

Then the operator AA is Picard operator.

3. Cauchy problem

We consider the fixed point system (4).
Let Af:C([t0h,b],Rm)C([t0h,b],Rm)A_{f}:C\left(\left[t_{0}-h,b\right],R^{m}\right)\rightarrow C\left(\left[t_{0}-h,b\right],R^{m}\right) given by the relation

Af(x)=(Af1(x1,,xm),,Afm(x1,,xm))A_{f}(x)=\left(A_{f_{1}}\left(x_{1},\ldots,x_{m}\right),\ldots,A_{f_{m}}\left(x_{1},\ldots,x_{m}\right)\right)

where

Afi(x1,,xm)(t):={φi(t),t[t0h,t0]φi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b]A_{f_{i}}\left(x_{1},\ldots,x_{m}\right)(t):=\left\{\begin{array}[]{l}\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ \varphi_{i}\left(t_{0}\right)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\\ \quad\cdot f_{i}\left(x_{1}(s-h),\ldots,x_{m}(s-h)\right)ds,t\in\left[t_{0},b\right]\end{array}\right.

We consider the Banach space C([t0h,b],Rm)C\left(\left[t_{0}-h,b\right],R^{m}\right) with the Chebyshev norm C\|\cdot\|_{C}. Let X=(C([t0h,b],Rm),C)X=\left(C\left(\left[t_{0}-h,b\right],R^{m}\right),\|\cdot\|_{C}\right).

We have the following result

Theorem 5. We suppose that
(i) the conditions (H1)(H4)\left(\mathrm{H}_{1}\right)-\left(\mathrm{H}_{4}\right) are satisfied;
(ii) Lf(bt0)i=1maibiebit0<1L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}<1.

Then the Cauchy problem (2)-(3) has in C([t0h,b],Rm)C\left(\left[t_{0}-h,b\right],R^{m}\right) a unique solution. Moreover, the operator Af:C([t0h,b],Rm)C([t0h,b],Rm)A_{f}:C\left(\left[t_{0}-h,b\right],R^{m}\right)\rightarrow C\left(\left[t_{0}-h,b\right],R^{m}\right) is c-Picard with

c=11Lf(bt0)i=1maibiebit0c=\frac{1}{1-L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}}

Proof. For t[t0h,t0]t\in\left[t_{0}-h,t_{0}\right], we have
|Afi(x1,,xm)(t)Afi(x¯1,,x¯m)(t)|=0,i=1,m¯\left|A_{f_{i}}\left(x_{1},\ldots,x_{m}\right)(t)-A_{f_{i}}\left(\bar{x}_{1},\ldots,\bar{x}_{m}\right)(t)\right|=0,i=\overline{1,m}.
For t[t0,b]t\in\left[t_{0},b\right], we have

|Afi(x1,,xm)(t)Afi(x¯1,,x¯m)(t)|=\displaystyle\left|A_{f_{i}}\left(x_{1},\ldots,x_{m}\right)(t)-A_{f_{i}}\left(\bar{x}_{1},\ldots,\bar{x}_{m}\right)(t)\right|=
=ait0tebi(st)[fi(x1(sh),,xm(sh))\displaystyle=a_{i}\mid\int_{t_{0}}^{t}e^{b_{i}(s-t)}\left[f_{i}\left(x_{1}(s-h),\ldots,x_{m}(s-h)\right)-\right.
fi(x¯1(sh),,x¯m(sh))]ds\displaystyle\left.\quad-f_{i}\left(\bar{x}_{1}(s-h),\ldots,\bar{x}_{m}(s-h)\right)\right]ds\mid\leq
aibiebit0(bt0)Lf(x1x¯1C++xmx¯mC),i=1,m¯\displaystyle\leq\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left(b-t_{0}\right)L_{f}\left(\left\|x_{1}-\bar{x}_{1}\right\|_{C}+\ldots+\left\|x_{m}-\bar{x}_{m}\right\|_{C}\right),i=\overline{1,m}

Then

Af(x1,,xm)Af(x¯1,,x¯m)C\displaystyle\left\|A_{f}\left(x_{1},\ldots,x_{m}\right)-A_{f}\left(\bar{x}_{1},\ldots,\bar{x}_{m}\right)\right\|_{C}\leq
Lf(bt0)i=1maibiebit0(x1,,xm)(x¯1,,x¯m)C\displaystyle\leq L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|\left(x_{1},\ldots,x_{m}\right)-\left(\bar{x}_{1},\ldots,\bar{x}_{m}\right)\right\|_{C}

So AfA_{f} is cc-Picard operator with c=11LAfc=\frac{1}{1-L_{A_{f}}}, where LAf=Lf(bt0)i=1maibiebit0L_{A_{f}}=L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}.

In what follows, we consider the following operator

Bf:C([t0h,b],Rm)C([t0h,b],Rm)B_{f}:C\left(\left[t_{0}-h,b\right],R^{m}\right)\rightarrow C\left(\left[t_{0}-h,b\right],R^{m}\right)

given by

Bf(x)=(Bf1(x1,,xm),,Bfm(x1,,xm)),B_{f}(x)=\left(B_{f_{1}}\left(x_{1},\ldots,x_{m}\right),\ldots,B_{f_{m}}\left(x_{1},\ldots,x_{m}\right)\right),

where

Bfi(x1,,xm)(t):={xi(t),t[t0h,t0]xi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b]B_{f_{i}}\left(x_{1},\ldots,x_{m}\right)(t):=\left\{\begin{array}[]{l}x_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ x_{i}\left(t_{0}\right)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\\ \cdot f_{i}\left(x_{1}(s-h),\ldots,x_{m}(s-h)\right)ds,t\in\left[t_{0},b\right]\end{array}\right.

Theorem 6. In the condition of Theorem 5, Bf:C([t0h,b],Rm)C([t0h,b],Rm)B_{f}:C\left(\left[t_{0}-h,b\right],R^{m}\right)\rightarrow C\left(\left[t_{0}-\right.\right.\left.h,b],R^{m}\right) is WPO.

Proof. The operator BfB_{f} is a continuous operator but it is not a contraction. Let take the following notation:

Xφi:={xiC([t0h,b],R)|xi|[t0h,t0]=φi,i=1,m¯}X_{\varphi_{i}}:=\left\{x_{i}\in C\left(\left[t_{0}-h,b\right],R\right)\left|x_{i}\right|_{\left[t_{0}-h,t_{0}\right]}=\varphi_{i},i=\overline{1,m}\right\}

Then we can write

C([t0h,b],Rm)=φiC([t0h,t0],R)Xφ1××Xφm,i=1,m¯C\left(\left[t_{0}-h,b\right],R^{m}\right)=\bigcup_{\varphi_{i}\in C\left(\left[t_{0}-h,t_{0}\right],R\right)}X_{\varphi_{1}}\times\ldots\times X_{\varphi_{m}},i=\overline{1,m} (6)

We have that Xφ1××XφmI(Bf)X_{\varphi_{1}}\times\ldots\times X_{\varphi_{m}}\in I\left(B_{f}\right) and Bf|Xφ1××Xφm\left.B_{f}\right|_{X_{\varphi_{1}}\times\ldots\times X_{\varphi_{m}}} is a Picard operator, because it is the operator which appears in the proof of the Theorem 5. By applying the Theorem 2, we obtain that BfB_{f} is WPO.

4. Increasing solutions of the system (2)

4.1. Inequalities of Caplygin type

Theorem 7. We suppose that
(a) the conditions of the Theorem 5 are satisfied;
(b) ui,viR,uivi,i=1,m¯u_{i},v_{i}\in R,u_{i}\leq v_{i},i=\overline{1,m} implies that

fi(u1,,um)fi(v1,,vm),i=1,m¯f_{i}\left(u_{1},\ldots,u_{m}\right)\leq f_{i}\left(v_{1},\ldots,v_{m}\right),i=\overline{1,m}

Let (x1,,xm)\left(x_{1},\ldots,x_{m}\right) be a solution of the system (2) and ( y1,,ymy_{1},\ldots,y_{m} ) a solution of the inequality system

yi(t)aifi(y1(th),,ym(th))biyi(t),t[t0,b]y_{i}^{\prime}(t)\leq a_{i}f_{i}\left(y_{1}(t-h),\ldots,y_{m}(t-h)\right)-b_{i}y_{i}(t),t\in\left[t_{0},b\right]

Then yi(t)xi(t),t[t0h,t0],i=1,m¯y_{i}(t)\leq x_{i}(t),t\in\left[t_{0}-h,t_{0}\right],i=\overline{1,m} implies that (y1,,ym)(x1,,xm)\left(y_{1},\ldots,y_{m}\right)\leq\left(x_{1},\ldots,x_{m}\right).

Proof. In the terms of the operator BfB_{f}, we have

(x1,,xm)=Bf(x1,,xm) and (y1,,ym)Bf(y1,,ym).\left(x_{1},\ldots,x_{m}\right)=B_{f}\left(x_{1},\ldots,x_{m}\right)\text{ and }\left(y_{1},\ldots,y_{m}\right)\leq B_{f}\left(y_{1},\ldots,y_{m}\right).

However, from the condition (b), we have that BfB_{f}^{\infty} is increasing,

(y1,,ym)\displaystyle\left(y_{1},\ldots,y_{m}\right) Bf(y1,,ym)=Bf(y~1|[t0h,t0],,y~m|[t0h,t0])\displaystyle\leq B_{f}^{\infty}\left(y_{1},\ldots,y_{m}\right)=B_{f}^{\infty}\left(\left.\widetilde{y}_{1}\right|_{\left[t_{0}-h,t_{0}\right]},\ldots,\left.\widetilde{y}_{m}\right|_{\left[t_{0}-h,t_{0}\right]}\right)\leq
Bf(x~1|[t0h,t0],,x~m|[t0h,t0])=(x1,,xm)\displaystyle\leq B_{f}^{\infty}\left(\left.\widetilde{x}_{1}\right|_{\left[t_{0}-h,t_{0}\right]},\ldots,\left.\widetilde{x}_{m}\right|_{\left[t_{0}-h,t_{0}\right]}\right)=\left(x_{1},\ldots,x_{m}\right)

Thus (y1,,ym)(x1,,xm)\left(y_{1},\ldots,y_{m}\right)\leq\left(x_{1},\ldots,x_{m}\right).
Here, we use the notation x~iXxi|[t0h,t0],i=1,m¯\widetilde{x}_{i}\in X_{\left.x_{i}\right|_{\left[t_{0}-h,t_{0}\right]}},i=\overline{1,m}.

4.2. Comparison theorem

In what follows we want to study the monotony of the solution of the problem (2)-(3), with respect to φi\varphi_{i} and fi,i=1,m¯f_{i},i=\overline{1,m}. We shall use the result below:

Lemma 1. (Abstract comparison Lemma). Let (X,d,)(X,d,\leq) be an ordered metric space and A,B,C:XXA,B,C:X\rightarrow X be such that:
(i) ABCA\leq B\leq C;
(ii) the operators A,B,CA,B,C are WPO;
(iii) the operator BB is increasing

Then xyzA(x)B(y)C(z)x\leq y\leq z\Rightarrow A^{\infty}(x)\leq B^{\infty}(y)\leq C^{\infty}(z).

In this case we can establish the theorem.

Theorem 8. Let fijC(Rm,R),i=1,m¯,j=1,2,3f_{i}^{j}\in C\left(R^{m},R\right),i=\overline{1,m},j=1,2,3.
We suppose that
(a) fi2(,,):RmRf_{i}^{2}(\cdot,\ldots,\cdot):R^{m}\rightarrow R is increasing, i=1,m¯i=\overline{1,m};
(b) fi1fi2fi3,i=1,m¯f_{i}^{1}\leq f_{i}^{2}\leq f_{i}^{3},i=\overline{1,m}.

Let xj=(x1j,xmj)x^{j}=\left(x_{1}^{j},\ldots x_{m}^{j}\right) be a solution of the equation

xi(t)=aifij(x1(th),,xm(th))bixi(t),x_{i}^{\prime}(t)=a_{i}f_{i}^{j}\left(x_{1}(t-h),\ldots,x_{m}(t-h)\right)-b_{i}x_{i}(t),

where t[t0,b],i=1,m¯,j=1,2,3t\in\left[t_{0},b\right],i=\overline{1,m},j=1,2,3.
If xi1(t)xi2(t)xi3(t),t[t0h,t0]x_{i}^{1}(t)\leq x_{i}^{2}(t)\leq x_{i}^{3}(t),t\in\left[t_{0}-h,t_{0}\right], then xi1xi2xi3,i=1,m¯x_{i}^{1}\leq x_{i}^{2}\leq x_{i}^{3},i=\overline{1,m}.

Proof. From Theorem 5, the operators Bfj,j=1,2,3B_{f}^{j},j=1,2,3 are weakly Picard operators.
Taking into consideration the condition (a), the operator Bf2B_{f}^{2} is increasing.
From (b) we have that Bf1Bf2Bf3B_{f}^{1}\leq B_{f}^{2}\leq B_{f}^{3}.
We note that (x1j,,xmj)=Bfj(x~1j,,x~mj),j=1,2,3\left(x_{1}^{j},\ldots,x_{m}^{j}\right)=B_{f}^{j\infty}\left(\widetilde{x}_{1}^{j},\ldots,\widetilde{x}_{m}^{j}\right),j=1,2,3. Now using the abstract comparison lemma, the proof is complete.

5. Data dependence: continuity

Consider the Cauchy problem (2)-(3) and suppose the conditions of the Theorem 5 are satisfied. Denote by x(,φ,f)=(x1(;φ1,f1),,xm(;φm,fm))x(\cdot,\varphi,f)=\left(x_{1}\left(\cdot;\varphi_{1},f_{1}\right),\ldots,x_{m}\left(\cdot;\varphi_{m},f_{m}\right)\right), the solution of this problem. We can state the following result:

Theorem 9. Let φij,fij,i=1,m¯,j=1,2\varphi_{i}^{j},f_{i}^{j},i=\overline{1,m},j=1,2 be as in the Theorem 5. Furthermore, we suppose that there exists ηi1,ηi2,i=1,m¯\eta_{i}^{1},\eta_{i}^{2},i=\overline{1,m} such that
(i) |φi1(t)φi2(t)|ηi1,t[t0h,t0],i=1,m¯\left|\varphi_{i}^{1}(t)-\varphi_{i}^{2}(t)\right|\leq\eta_{i}^{1},\forall t\in\left[t_{0}-h,t_{0}\right],i=\overline{1,m};
(ii) |fi1(u1,,um)fi2(u1,,um)|ηi2,i=1,m¯,uiR\left|f_{i}^{1}\left(u_{1},\ldots,u_{m}\right)-f_{i}^{2}\left(u_{1},\ldots,u_{m}\right)\right|\leq\eta_{i}^{2},i=\overline{1,m},u_{i}\in R.

Then

|xi(t;φi1,fi1)xi(t;φi2,fi2)|i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi21Lf(bt0)i=1maibiebit0,\left|x_{i}\left(t;\varphi_{i}^{1},f_{i}^{1}\right)-x_{i}\left(t;\varphi_{i}^{2},f_{i}^{2}\right)\right|\leq\frac{\sum_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}\left(t-t_{0}\right)}+\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}^{2}}{1-L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2),i=1,m¯L_{f}=\max\left(L_{f^{1}},L_{f^{2}}\right),i=\overline{1,m}.

Proof. Consider the operators Aφij,fij,i=1,m¯,j=1,2A_{\varphi_{i}^{j},f_{i}^{j}},i=\overline{1,m},j=1,2. From Theorem 5 these operators are contractions.

Additionally

Aφi1,fi1(x1,,xm)Aφi2,fi2(x1,,xm)C\displaystyle\left\|A_{\varphi_{i}^{1},f_{i}^{1}}\left(x_{1},\ldots,x_{m}\right)-A_{\varphi_{i}^{2},f_{i}^{2}}\left(x_{1},\ldots,x_{m}\right)\right\|_{C}\leq
i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi2,\displaystyle\leq\sum_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}\left(t-t_{0}\right)}+\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}^{2},

x=(x1,,xm)C([t0h,b],Rm)\forall x=\left(x_{1},\ldots,x_{m}\right)\in C\left(\left[t_{0}-h,b\right],R^{m}\right).
Now the proof follows from the Theorem 1, with A:=Aφi1,fi1,B=Aφi2,fi2,η=i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi2A:=A_{\varphi_{i}^{1},f_{i}^{1}},B=A_{\varphi_{i}^{2},f_{i}^{2}},\eta=\sum_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}\left(t-t_{0}\right)}+\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}^{2} and α:=LAf=Lf(bt0)i=1maibiebit0\alpha:=L_{A_{f}}=L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}} where Lf=max(Lf1,Lf2),i=1,m¯L_{f}=\max\left(L_{f^{1}},L_{f^{2}}\right),i=\overline{1,m}.

From the Theorem above we have:

Theorem 10. Let fi1f_{i}^{1} and fi2f_{i}^{2} be as in the Theorem 5, i=1,m¯i=\overline{1,m}. Let SBfi1,SBfi2S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}} be the solution set of system (2) corresponding to fi1f_{i}^{1} and fi2,i=1,m¯f_{i}^{2},i=\overline{1,m}. Suppose that there exists ηi>0,i=1,m¯\eta_{i}>0,i=\overline{1,m} such that

|fi1(u1,,um)fi2(u1,,um)|ηi\left|f_{i}^{1}\left(u_{1},\ldots,u_{m}\right)-f_{i}^{2}\left(u_{1},\ldots,u_{m}\right)\right|\leq\eta_{i} (7)

for all uiR,i=1,m¯u_{i}\in R,i=\overline{1,m}.
Then

HC(SBfi1,SBfi2)(bt0)i=1maibiebit0ηi1Lf(bt0)i=1maibiebit0,H_{\|\cdot\|_{C}}\left(S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}}\right)\leq\frac{\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}}{1-L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2)L_{f}=\max\left(L_{f^{1}},L_{f^{2}}\right) and HCH_{\|\cdot\|_{C}} denotes the Pompeiu-Housdorff functional with respect to C\|\cdot\|_{C} on C([t0h,b],Rm)C\left(\left[t_{0}-h,b\right],R^{m}\right).

Proof. In condition of the Theorem 5, the operators Bfi1B_{f_{i}^{1}} and Bfi2,i=1,m¯B_{f_{i}^{2}},i=\overline{1,m} are c1c_{1}-WPO and c2c_{2}-weakly Picard operators.

Let

Xφi:={xiC([t0h,b],R)|xi|[t0τ1,t0]=φi,i=1,m¯}.X_{\varphi_{i}}:=\left\{x_{i}\in C\left(\left[t_{0}-h,b\right],R\right)\left|x_{i}\right|_{\left[t_{0}-\tau_{1},t_{0}\right]}=\varphi_{i},i=\overline{1,m}\right\}.

It is clear that Bfi1|Xφi=Afi1,Bfi2|Xφi=Afi2\left.B_{f_{i}^{1}}\right|_{X_{\varphi_{i}}}=A_{f_{i}^{1}},\left.B_{f_{i}^{2}}\right|_{X_{\varphi_{i}}}=A_{f_{i}^{2}}. So, from Theorem 2 and Theorem 5 we have

Bfi12(x1,,xm)Bfi1(x1,,xm)C\displaystyle\left\|B_{f_{i}^{1}}^{2}\left(x_{1},\ldots,x_{m}\right)-B_{f_{i}^{1}}\left(x_{1},\ldots,x_{m}\right)\right\|_{C}\leq
Lf1(bt0)i=1maibiebit0Bfi1(x1,,xm)(x1,,xm)C,\displaystyle\leq L_{f^{1}}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|B_{f_{i}^{1}}\left(x_{1},\ldots,x_{m}\right)-\left(x_{1},\ldots,x_{m}\right)\right\|_{C},
Bfi22(x1,,xm)Bfi2(x1,,xm)C\displaystyle\left\|B_{f_{i}^{2}}^{2}\left(x_{1},\ldots,x_{m}\right)-B_{f_{i}^{2}}\left(x_{1},\ldots,x_{m}\right)\right\|_{C}\leq
Lf2(bt0)i=1maibiebit0Bfi2(x1,,xm)(x1,,xm)C,\displaystyle\leq L_{f^{2}}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|B_{f_{i}^{2}}\left(x_{1},\ldots,x_{m}\right)-\left(x_{1},\ldots,x_{m}\right)\right\|_{C},

for all (x1,,xm)C([t0h,b],Rm),i=1,m¯\left(x_{1},\ldots,x_{m}\right)\in C\left(\left[t_{0}-h,b\right],R^{m}\right),i=\overline{1,m}.
Now, choosing

α1=Lf1(bt0)i=1maibiebit0 and\displaystyle\alpha_{1}=L_{f^{1}}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\text{ and }
α2=Lf2(bt0)i=1maibiebit0\displaystyle\alpha_{2}=L_{f^{2}}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}

we get that Bfi1B_{f_{i}^{1}} and Bfi2B_{f_{i}^{2}} are c1c_{1}-weakly Picard operators and c2c_{2}-weakly Picard operators with c1=(1α1)1c_{1}=\left(1-\alpha_{1}\right)^{-1} and c2=(1α2)1c_{2}=\left(1-\alpha_{2}\right)^{-1}. From (7) we obtain that

Bfi1(x1,,xm)Bfi2(x1,,xm)C(bt0)i=1maibiebit0ηi\left\|B_{f_{i}^{1}}\left(x_{1},\ldots,x_{m}\right)-B_{f_{i}^{2}}\left(x_{1},\ldots,x_{m}\right)\right\|_{C}\leq\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}

(x1,,xm)C([t0h,b],Rm),i=1,m¯\forall\left(x_{1},\ldots,x_{m}\right)\in C\left(\left[t_{0}-h,b\right],R^{m}\right),i=\overline{1,m}. Applying Theorem 3 we have that

HC(SBfi1,SBfi2)(bt0)i=1maibiebit0ηi1Lf(bt0)i=1maibiebit0,H_{\|\cdot\|_{C}}\left(S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}}\right)\leq\frac{\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}}{1-L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2)L_{f}=\max\left(L_{f^{1}},L_{f^{2}}\right) and HCH_{\|\cdot\|_{C}} is the Pompeiu-Housdorff functional with respect to C\|\cdot\|_{C} on C([t0h,b],Rm)C\left(\left[t_{0}-h,b\right],R^{m}\right). \square

6. Data dependence: differentiability

Consider the following differential system with parameter

xi(t)=aifi(x1(th),,xm(th);λ)bixi(t),t[t0,b],i=1,m¯\displaystyle x_{i}^{\prime}(t)=a_{i}f_{i}\left(x_{1}(t-h),\ldots,x_{m}(t-h);\lambda\right)-b_{i}x_{i}(t),t\in\left[t_{0},b\right],i=\overline{1,m} (8)
xi(t)=φi(t),t[t0h,t0],i=1,m¯\displaystyle x_{i}(t)=\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right],i=\overline{1,m} (9)

Suppose that we have satisfied the following conditions:
(C1)t0<b,h>0,JR\left(\mathrm{C}_{1}\right)t_{0}<b,h>0,J\subset R a compact interval;
(C2)fiC1(Rm×J,R),i=1,m¯\left(\mathrm{C}_{2}\right)f_{i}\in C^{1}\left(R^{m}\times J,R\right),i=\overline{1,m};
(C3)φiC([t0h,t0],R),i=1,m¯;\left(\mathrm{C}_{3}\right)\varphi_{i}\in C\left(\left[t_{0}-h,t_{0}\right],R\right),i=\overline{1,m};
(C4)\left(\mathrm{C}_{4}\right) there exists Lf>0,i=1,m¯L_{f}>0,i=\overline{1,m} such that

|fi(u1,,um;λ)ui|Lf,uiR,i=1,m¯,λJ;\left|\frac{\partial f_{i}\left(u_{1},\ldots,u_{m};\lambda\right)}{\partial u_{i}}\right|\leq L_{f},u_{i}\in R,i=\overline{1,m},\lambda\in J;

( C5\mathrm{C}_{5} ) Lf(bt0)i=1maibiebit0<1L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}<1.
Then, from Theorem 5, we have that the problem (2)-(3) has a unique solution, (x1(,λ),,xm(,λ))\left(x_{1}^{*}(\cdot,\lambda),\ldots,x_{m}^{*}(\cdot,\lambda)\right).

We prove that xi(,λ)C1(J),t[t0h,b],i=1,m¯x_{i}^{*}(\cdot,\lambda)\in C^{1}(J),\forall t\in\left[t_{0}-h,b\right],i=\overline{1,m}.
For this we consider the system

xi(t,λ)=aifi(x1(th;λ),,xm(th;λ);λ)bixi(t;λ),x_{i}^{\prime}(t,\lambda)=a_{i}f_{i}\left(x_{1}(t-h;\lambda),\ldots,x_{m}(t-h;\lambda);\lambda\right)-b_{i}x_{i}(t;\lambda), (10)

t[t0,b],λJ,xiC([t0h,b]×J,R)C1([t0,b]×J,R),i=1,m¯t\in\left[t_{0},b\right],\lambda\in J,x_{i}\in C\left(\left[t_{0}-h,b\right]\times J,R\right)\cap C^{1}\left(\left[t_{0},b\right]\times J,R\right),i=\overline{1,m}.

Theorem 11. Consider the problem (10)-(9), and suppose the conditions ( C1\mathrm{C}_{1} )(C5)\left(\mathrm{C}_{5}\right) hold. Then,
(i) (10)-(9) has a unique solution (x1(,λ),,xm(,λ))\left(x_{1}^{*}(\cdot,\lambda),\ldots,x_{m}^{*}(\cdot,\lambda)\right), in C([t0h,b]×J,Rm);C\left(\left[t_{0}-h,b\right]\times\right.\left.J,R^{m}\right);
(ii) (x1(,λ),,xm(,λ))C1(J),t[t0h,b],i=1,m¯\left(x_{1}^{*}(\cdot,\lambda),\ldots,x_{m}^{*}(\cdot,\lambda)\right)\in C^{1}(J),\forall t\in\left[t_{0}-h,b\right],i=\overline{1,m}.

Proof. The problem (10)-(9) is equivalent with the following functional-integral equation

xi(t;λ)={φi(t),t[t0h,t0]φi(t)ebi(tt0)+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ),t[t0,b]x_{i}(t;\lambda)=\left\{\begin{array}[]{l}\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ \varphi_{i}(t)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}\left(x_{1}(s-h;\lambda),\ldots,\right.\\ \left.\quad x_{m}(s-h;\lambda);\lambda\right),t\in\left[t_{0},b\right]\end{array}\right.

Now let take the operator

A:C([t0h,b]×J,Rm)C([t0h,b]×J,Rm)A:C\left(\left[t_{0}-h,b\right]\times J,R^{m}\right)\rightarrow C\left(\left[t_{0}-h,b\right]\times J,R^{m}\right)

given by

A(x1,,xm)=(A1(x1,,xm),,Am(x1,,xm)),A\left(x_{1},\ldots,x_{m}\right)=\left(A_{1}\left(x_{1},\ldots,x_{m}\right),\ldots,A_{m}\left(x_{1},\ldots,x_{m}\right)\right),

where

Ai(x1,,xm)(t;λ):={φi(t),t[t0h,t0]φi(t)ebi(tt0)+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ),t[t0,b]A_{i}\left(x_{1},\ldots,x_{m}\right)(t;\lambda):=\left\{\begin{array}[]{l}\varphi_{i}(t),t\in\left[t_{0}-h,t_{0}\right]\\ \varphi_{i}(t)e^{-b_{i}\left(t-t_{0}\right)}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\\ \cdot f_{i}\left(x_{1}(s-h;\lambda),\ldots,x_{m}(s-h;\lambda);\lambda\right),t\in\left[t_{0},b\right]\end{array}\right.

Let X=C([t0τ1,b]×J,Rm)X=C\left(\left[t_{0}-\tau_{1},b\right]\times J,R^{m}\right).
It is clear, from the proof of the Theorem 5, that in the condition (C1)(C5)\left(\mathrm{C}_{1}\right)-\left(\mathrm{C}_{5}\right), the operator A:(X,C)(X,C)A:\left(X,\|\cdot\|_{C}\right)\rightarrow\left(X,\|\cdot\|_{C}\right) is Picard operator.

Let (x1,,xm)\left(x_{1}^{*},\ldots,x_{m}^{*}\right) be the unique fixed point of AA.
Supposing that there exists xiλ,i=1,m¯\frac{\partial x_{i}^{*}}{\partial\lambda},i=\overline{1,m}, from (11), we have that

xiλ=\displaystyle\frac{\partial x_{i}^{*}}{\partial\lambda}= ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)u1x1(sh,λ)λ𝑑s+\displaystyle a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial u_{1}}\cdot\frac{\partial x_{1}^{*}(s-h,\lambda)}{\partial\lambda}ds+\ldots
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)umxm(sh,λ)λ𝑑s+\displaystyle+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial u_{m}}\cdot\frac{\partial x_{m}^{*}(s-h,\lambda)}{\partial\lambda}ds+
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)λ𝑑s\displaystyle+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial\lambda}ds

for all t[t0,b],λJ,i=1,m¯t\in\left[t_{0},b\right],\lambda\in J,i=\overline{1,m}.
This relation suggest us to consider the following operator

C\displaystyle C :X×XX,\displaystyle:X\times X\rightarrow X,
(x1,,xm,u1,,um)\displaystyle\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right) C(x1,,xm,u1,,um),\displaystyle\rightarrow C\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right),

where Ci(x1,,xm,u1,,um)(t;λ)=0C_{i}\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right)(t;\lambda)=0 for t[t0h,t0],λJ,i=1,m¯t\in\left[t_{0}-h,t_{0}\right],\lambda\in J,i=\overline{1,m} and

Ci(x1,,xm,u1,,um)(t;λ):=\displaystyle C_{i}\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right)(t;\lambda)=
=ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)u1u1(sh;λ)𝑑s+\displaystyle=a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial u_{1}}\cdot u_{1}(s-h;\lambda)ds+\ldots
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)umum(sh;λ)𝑑s+\displaystyle\quad+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial u_{m}}\cdot u_{m}(s-h;\lambda)ds+
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)λ𝑑s\displaystyle\quad+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}\left(x_{1}^{*}(s-h;\lambda),\ldots,x_{m}^{*}(s-h;\lambda);\lambda\right)}{\partial\lambda}ds

for t[t0,b],λJ,i=1,m¯t\in\left[t_{0},b\right],\lambda\in J,i=\overline{1,m}.

In this way we have the triangular operator

D:X×XX×X,\displaystyle D:X\times X\rightarrow X\times X,
(x1,,xm,u1,,um)(A(x1,,xm),C(x1,,xm,u1,,um)),\displaystyle\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right)\rightarrow\left(A\left(x_{1},\ldots,x_{m}\right),C\left(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}\right)\right),

where AA is Picard operator and C(x1,,xm,,,):YYC\left(x_{1},\ldots,x_{m},\cdot,\ldots,\cdot\right):Y\rightarrow Y is LCL_{C}-contraction with LC=Lf(bt0)i=1maibiebit0L_{C}=L_{f}\left(b-t_{0}\right)\sum_{i=1}^{m}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}.

From Theorem 4 we have that the operator DD is Picard operator, i.e. the sequences

(x1,n+1,,xm,n+1):=A(x1,n,,xm,n)\displaystyle\left(x_{1,n+1},\ldots,x_{m,n+1}\right)=A\left(x_{1,n},\ldots,x_{m,n}\right)
(u1,n+1,,um,n+1):=C(x1,n,,xm,n,u1,n,,um,n)\displaystyle\left(u_{1,n+1},\ldots,u_{m,n+1}\right)=C\left(x_{1,n},\ldots,x_{m,n},u_{1,n},\ldots,u_{m,n}\right)

nNn\in N, converges uniformly, with respect to tX,λJt\in X,\lambda\in J, to (x1,,xm,u1,,um)FD\left(x_{1}^{*},\ldots,x_{m}^{*},u_{1}^{*},\ldots,u_{m}^{*}\right)\in F_{D}, for all (x1,0,,xm,0)X,(u1,0,,um,0)X\left(x_{1,0},\ldots,x_{m,0}\right)\in X,\left(u_{1,0},\ldots,u_{m,0}\right)\in X.

If we take

x1,0=0,,xm,0=0u1,0=x1,0λ=0,,um,0=xm,0λ=0\begin{gathered}x_{1,0}=0,\ldots,x_{m,0}=0\\ u_{1,0}=\frac{\partial x_{1,0}}{\partial\lambda}=0,\ldots,u_{m,0}=\frac{\partial x_{m,0}}{\partial\lambda}=0\end{gathered}

then

u1,1=x1,1λ,,um,1=xm,1λu_{1,1}=\frac{\partial x_{1,1}}{\partial\lambda},\ldots,u_{m,1}=\frac{\partial x_{m,1}}{\partial\lambda}

By induction we prove that

u1,n=x1,nλ,,um,n=xm,nλ,nN.u_{1,n}=\frac{\partial x_{1,n}}{\partial\lambda},\cdots,u_{m,n}=\frac{\partial x_{m,n}}{\partial\lambda},\forall n\in N.

So

x1,n unif x1,,xm,n unif xm, as n,\displaystyle x_{1,n}\xrightarrow{\text{ unif }}x_{1}^{*},\cdots,x_{m,n}\xrightarrow{\text{ unif }}x_{m}^{*},\text{ as }n\rightarrow\infty,
x1,nλ unif u1,,xm,nλ unif um, as n.\displaystyle\frac{\partial x_{1,n}}{\partial\lambda}\xrightarrow{\text{ unif }}u_{1}^{*},\cdots,\frac{\partial x_{m,n}}{\partial\lambda}\xrightarrow{\text{ unif }}u_{m}^{*},\text{ as }n\rightarrow\infty.

From a Weierstrass argument we have that there exists xiλ,i=1,m¯\frac{\partial x_{i}^{*}}{\partial\lambda},i=\overline{1,m} and

x1λ=u1,,xmλ=um\frac{\partial x_{1}^{*}}{\partial\lambda}=u_{1}^{*},\ldots,\frac{\partial x_{m}^{*}}{\partial\lambda}=u_{m}^{*}

References

  1. 1.

    J. K. Hale, Introduction to functional differential equations, Springer-Verlag, 1993.

  2. 2.

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    V. Mureşan, Functional-Integral Equations, Mediamira, Cluj-Napoca, 2003.

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    D. Otrocol, Data dependence for the solution of a Lotka-Volterra system with two delays, Mathematica 48(2006), No.71, 61-68.

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    D. Otrocol, Lotka-Volterra system with two delays via weakly Picard operators, Nonlinear Analysis Forum 10(2005), No.2, 193-199.

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    I. A. Rus, Picard operators and applications, J. Scientiae Mathematicae Japonicae 58(2003), No.1, 191-219.

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    I. A. Rus, Generalized Contractions and Applications, Cluj University Press, 2001.

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    I. A. Rus, Weakly Picard operators and applications, Seminar of Fixed Point Theory, ClujNapoca, 2(2001), 41-58.

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    M. Saidalieva, Modelling of regulation mechanism of cellular communities, J. Scientiae Mathematicae Japonicae 8(2003), 463-469.

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Diana Otrocol received her Ph.D at Babeş-Bolyai University under the direction of Petru Blaga. Now she is a research assistant at the Tiberiu Popoviciu Institute of Numerical Analysis. Her research interests focus on the fixed point theory and numerical analysis.

Tiberiu Popoviciu Institute of Numerical Analysis, Cluj-Napoca, Romania
e-mail: dotrocol@ictp.acad.ro

A Differential equation with delay from biology

Diana Otrocol
Abstract.

The purpose of this paper is to present a differential equation with delay from biological excitable medium. Existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results for the solution of the Cauchy problem of biological excitable medium are obtained using weakly Picard operator theory.

AMS Mathematics Subject Classification : 47H10, 47N20.

Key words and phrases : excitable medium, differential-delay equations, weakly Picard operator.


This work has been supported by MEdC-ANCS under grant 2-CEx06-11-96/19.09.2006.

1. Introduction

In recent years the theory of excitable medium has rapidly developed and its results have been applied in various areas: chemistry, biology, ecology, electric engineering, populations dynamics, cardiology, neurology. At present, different approaches for the mathematical description of biological excitable medium by means of partial-differential equation, functional-differential, functional and discrete equations are applied. The papers [3], [4], [11] has offered the opportunity for understanding the normal regulation of living systems as well as its anomalies.

The activity of the ii-th element of the excitable medium can be described by the following equation:

(1) xi(t)=aifi(x1(th),,xm(th))bixi(t)x_{i}^{\prime}(t)=a_{i}f_{i}(x_{1}(t-h),\ldots,x_{m}(t-h))-b_{i}x_{i}(t)

where xi(t)x_{i}(t) is the activity of the ii-th element; aia_{i} is the functional parameter of the ii-th element; fi()f_{i}(\cdot) is the feedback function; bib_{i} is the decay constant, i=1,m¯.i=\overline{1,m}.

The aim of this paper is to study the following problem

(2) xi(t)=aifi(x1(th),,xm(th))bixi(t),x_{i}^{\prime}(t)=a_{i}f_{i}(x_{1}(t-h),\ldots,x_{m}(t-h))-b_{i}x_{i}(t),

t[t0,b],i=1,m¯,t\in[t_{0},b],i=\overline{1,m}, with initial conditions

(3) xi(t)=φi(t),t[t0h,t0],x_{i}(t)=\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}],

where

  1. (H1)

    t0<b,h>0,t0,b,hR;t_{0}<b,\ h>0,\ t_{0},b,h\in R;

  2. (H2)

    fiC(Rm,R),i=1,m¯;f_{i}\in C(R^{m},R),\ i=\overline{1,m};

  3. (H3)

    φiC([t0h,t0],R),i=1,m¯;\varphi_{i}\in C([t_{0}-h,t_{0}],R),\ i=\overline{1,m};

  4. (H4)

    there exists Lf>0,L_{f}>0, such as:

    |fi(u1,,um)fi(v1,,vm)|Lfi=1m|uivi|,\left|f_{i}(u_{1},\ldots,u_{m})-f_{i}(v_{1},\ldots,v_{m})\right|\leq L_{f}\sum_{i=1}^{m}\left|u_{i}-v_{i}\right|,

    for all ui,viR,i=1,m¯.u_{i},v_{i}\in R,i=\overline{1,m}.

By a solution of the problem (2)–(3) we understand the function x=(x1,,xm)Rmx\!=\!(x_{1},\!\ldots\!,x_{m})\\ \in R^{m} with xiC([t0h,b],R)C1([t0,b],R),i=1,m¯x_{i}\in C([t_{0}-h,b],R)\cap C^{1}([t_{0},b],R),\ i=\overline{1,m} which satisfies (2)–(3).

The problem (2)–(3) is equivalent with the following fixed point system:

(4) xi(t)={φi(t),t[t0h,t0],φi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b],x_{i}(t)\!=\!\left\{\!\begin{array}[c]{l}\!\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}],\\ \!\varphi_{i}(t_{0})e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}(x_{1}(s-h),\ldots,\\ \ \ x_{m}(s-h))ds,\ t\!\in\![t_{0},b],\end{array}\right.

where xiC([t0h,b],R),i=1,m¯.x_{i}\in C([t_{0}-h,b],R),\ i=\overline{1,m}.

On the other hand, the system (2) is equivalent with

(5) xi(t)={xi(t),t[t0h,t0],xi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b],x_{i}(t)\!=\!\left\{\!\begin{array}[c]{l}\!x_{i}(t),\ t\in[t_{0}-h,t_{0}],\\ \!x_{i}(t_{0})e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}(x_{1}(s-h),\ldots,\\ \ \ x_{m}(s-h))ds,\ t\!\in\![t_{0},b],\end{array}\right.

where xiC([t0h,b],R),i=1,m¯.x_{i}\in C([t_{0}-h,b],R),\ i=\overline{1,m}.

In this paper we apply the weakly Picard operators technique to study the systems (4) and (5).

2. Weakly Picard operators

I.A. Rus introduced the Picard operators class (PO) and the weakly Picard operators class (WPO) for the operators defined on a metric space and he gave basic notations, definitions and results in this field in many papers [8][10]. Some problems concerning this techniques were study in [5], [12], [6], [7].

Let (X,d)(X,d) be a metric space and A:XXA:X\rightarrow X an operator. We shall use the following notations:

FA:={xXA(x)=x}F_{A}:=\{x\in X\mid A(x)=x\} - the fixed point set of AA;

I(A):={YXA(Y)Y,Y}I(A):=\{Y\subset X\mid A(Y)\subset Y,Y\neq\emptyset\} - the family of the nonempty invariant subset of AA;

An+1:=AAn,A0=1X,A1=A,nNA^{n+1}:=A\circ A^{n},\;A^{0}=1_{X},\;A^{1}=A,\;n\in N;

P(X):={YXY}P(X):=\{Y\subset X\mid Y\neq\emptyset\} - the set of the parts of X;X;

H(Y,Z):=max{supyYinfzZd(y,z),supzZinfyYd(y,z)}H(Y,Z):=\max\{\underset{y\in Y}{\sup}\underset{z\in Z}{\inf}d(y,z),\underset{z\in Z}{\sup}\underset{y\in Y}{\inf}d(y,z)\} -the Pompeiu–Housdorff functional on P(X)×P(X)P(X)\times P(X).

Definition 1.

([8], [10]) Let (X,d)(X,d) be a metric space. An operator A:XXA:X\rightarrow X is a Picard operator (PO) if there exists xXx^{\ast}\in X such that:

  1. (i)

    FA={x};F_{A}=\{x^{\ast}\};

  2. (ii)

    the sequence (An(x0))nN(A^{n}(x_{0}))_{n\in N} converges to xx^{\ast} for all x0Xx_{0}\in X.

Remark 1.

([8], [10]) Accordingly to the definition, the contraction principle insures that, if A:XXA:X\rightarrow X is an α\alpha -contraction on the complete metric space XX, then it is a Picard operator.

Theorem 1.

([8], [10]) (Data dependence theorem). Let (X,d)(X,d) be a complete metric space and A,B:XXA,B:X\rightarrow X two operators. We suppose that

  1. (i)

    the operator AA is a α\alpha -contraction;

  2. (ii)

    FB;F_{B}\neq\emptyset;

  3. (iii)

    there exists η>0\eta>0 such that

    d(A(x),B(x))η,xX.d(A(x),B(x))\leq\eta,\ \forall x\in X.

Then, if FA={xA}F_{A}=\{x_{A}^{\ast}\} and xBFB,x_{B}^{\ast}\in F_{B}, we have

d(xA,xB)η1α.d(x_{A}^{\ast},x_{B}^{\ast})\leq\frac{\eta}{1-\alpha}.
Definition 2.

([8], [10]) Let (X,d)(X,d) be a metric space. An operator A:XXA:X\rightarrow X is a weakly Picard operator (WPO) if the sequence (An(x))nN(A^{n}(x))_{n\in N} converges for all xXx\in X, and its limit (which may depend on xx) is a fixed point of AA.

Theorem 2.

([8], [10]) Let (X,d)(X,d) be a metric space and A:XXA:X\rightarrow X an operator. The operator AA is weakly Picard operator if and only if there exists a partition of XX,

X=λΛXλX=\underset{\lambda\in\Lambda}{\cup}X_{\lambda}

where Λ\Lambda is the indices set of partition, such that:

  1. (a)

    XλI(A),λΛX_{\lambda}\in I(A),\ \lambda\in\Lambda;

  2. (b)

    A|Xλ:XλXλA|_{X_{\lambda}}:X_{\lambda}\rightarrow X_{\lambda} is a Picard operator for all λΛ\lambda\in\Lambda.

Definition 3.

([8], [10]) If AA is weakly Picard operator then we consider the operator AA^{\infty} defined by

A:XX,A(x):=limnAn(x).A^{\infty}:X\rightarrow X,\ A^{\infty}(x):=\underset{n\rightarrow\infty}{\lim}A^{n}(x).

It is clear that A(X)=FA.A^{\infty}(X)=F_{A}.

Definition 4.

([8], [10]) Let AA be a weakly Picard operator and c>0.c>0. The operator AA\ is cc -weakly Picard operator if

d(x,A(x))cd(x,A(x)),xX.d(x,A^{\infty}(x))\leq cd(x,A(x)),\ \forall x\in X.
Example 1.

([8], [10]) Let (X,d)(X,d) be a complete metric space and A:XXA:X\rightarrow X a continuous operator. We suppose that there exists α[0,1)\alpha\in[0,1) such that

d(A2(x),A(x))α(x,A(x)),xX.d(A^{2}(x),A(x))\leq\alpha(x,A(x)),\ \forall x\in X.

Then AA is cc -weakly Picard operator with c=11α.c=\dfrac{1}{1-\alpha}.

Theorem 3.

([8], [10]) Let (X,d)(X,d) be a metric space and Ai:XX,i=1,2.A_{i}:X\rightarrow X,\ i=1,2. Suppose that

  1. (i)

    the operator AiA_{i} is cic_{i}-weakly Picard operator, i=1,2;i\!=\!1,2;

  2. (ii)

    there exists η>0\eta>0 such that

    d(A1(x),A2(x))η,xX.d(A_{1}(x),A_{2}(x))\leq\eta,\ \forall x\in X.

Then H(FA1,FA2)ηmax(c1,c2).H(F_{A_{1}},F_{A_{2}})\leq\eta\max(c_{1},c_{2}).

Theorem 4.

([8], [10]) (Fibre contraction principle). Let (X,d)(X,d) and (Y,ρ)(Y,\rho) be two metric spaces and A:X×YX×Y,A=(B,C),(B:XX,C:X×YY)A:X\times Y\rightarrow X\times Y,\ A=(B,C),\ (\ B:X\rightarrow X,\ C:X\times Y\rightarrow Y\ ) a triangular operator. We suppose that

  1. (i)

    (Y,ρ)(Y,\rho) is a complete metric space;

  2. (ii)

    the operator BB is Picard operator;

  3. (iii)

    there exists l[0,1)l\in[0,1) such that C(x,):YYC(x,\cdot):Y\rightarrow Y is a ll-contraction, for all xXx\in X;

  4. (iv)

    if (x,y)FA(x^{\ast},y^{\ast})\in F_{A}, then C(,y)C(\cdot,y^{\ast}) is continuous in xx^{\ast}.

Then the operator AA is Picard operator.

3. Cauchy problem

We consider the fixed point system (4).

Let Af:C([t0h,b],Rm)C([t0h,b],Rm)A_{f}:C([t_{0}-h,b],R^{m})\rightarrow C([t_{0}-h,b],R^{m}) given by the relation

Af(x)=(Af1(x1,,xm),,Afm(x1,,xm)),A_{f}(x)=(A_{f_{1}}(x_{1},\ldots,x_{m}),\ldots,A_{f_{m}}(x_{1},\ldots,x_{m})),

where

Afi(x1,,xm)(t):={φi(t),t[t0h,t0],φi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b].A_{f_{i}}(x_{1},\ldots,x_{m})(t):=\left\{\!\begin{array}[c]{l}\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}],\\ \varphi_{i}(t_{0})e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\cdot\\ \ \ \cdot f_{i}(x_{1}(s-h),\ldots,x_{m}(s-h))ds,t\in[t_{0},b].\end{array}\right.

We consider the Banach space C([t0h,b],Rm)C([t_{0}-h,b],R^{m}\mathbb{)} with the Chebyshev normC.\ \left\|\cdot\right\|_{C}. Let X=(C([t0h,b],Rm),C)X=(C([t_{0}-h,b],R^{m}),\left\|\cdot\right\|_{C}).

We have the following result

Theorem 5.

We suppose that

  1. (i)

    the conditions (H1{}_{\text{1}})–(H4{}_{\text{4}}) are satisfied;

  2. (ii)

    Lf(bt0)i=1maibiebit0<1.L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}<1.

Then the Cauchy problem (2)–(3) has in C([t0h,b],Rm)C([t_{0}-h,b],R^{m}) a unique solution. Moreover, the operator Af:C([t0h,b],Rm)C([t0h,b],Rm)A_{f}:C([t_{0}-h,b],R^{m})\rightarrow C([t_{0}-h,b],R^{m}) is cc-Picard with

c=11Lf(bt0)i=1maibiebit0.c=\frac{1}{1-L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}}.
Proof.

For t[t0h,t0],t\in[t_{0}-h,t_{0}], we have
|Afi(x1,,xm)(t)Afi(x¯1,,x¯m)(t)|=0,i=1,m¯.\left|A_{f_{i}}(x_{1},\ldots,x_{m})(t)-A_{f_{i}}(\overline{x}_{1},\ldots,\overline{x}_{m})(t)\right|=0,\ i=\overline{1,m}.

For t[t0,b]t\in[t_{0},b], we have

|Afi(x1,,xm)(t)Afi(x¯1,,x¯m)(t)|=\displaystyle\left|A_{f_{i}}(x_{1},\ldots,x_{m})(t)-A_{f_{i}}(\overline{x}_{1},\ldots,\overline{x}_{m})(t)\right|=
=ai|t0tebi(st)[fi(x1(sh),,xm(sh))\displaystyle=a_{i}\left|\int_{t_{0}}^{t}e^{b_{i}(s-t)}[f_{i}(x_{1}(s-h),\ldots,x_{m}(s-h))-\right.
fi(x¯1(sh),,x¯m(sh))]ds|\displaystyle\left.\ \ -f_{i}(\overline{x}_{1}(s-h),\ldots,\overline{x}_{m}(s-h))]ds\right|\leq
aibiebit0(bt0)Lf(x1x¯1C++xmx¯mC),i=1,m¯.\displaystyle\leq\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}(b-t_{0})L_{f}(\left\|x_{1}-\overline{x}_{1}\right\|_{C}+\ldots+\left\|x_{m}-\overline{x}_{m}\right\|_{C}),i=\overline{1,m}.

Then

Af(x1,,xm)Af(x¯1,,x¯m)CLf(bt0)i=1maibiebit0(x1,,xm)(x¯1,,x¯m)C.\begin{array}[c]{l}\left\|A_{f}(x_{1},\!\ldots\!,x_{m})\!-\!A_{f}(\overline{x}_{1},\!\ldots\!,\overline{x}_{m})\right\|_{C}\leq\\ \leq L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|(x_{1},\ldots,x_{m})\!\!-\!\!(\overline{x}_{1},\ldots,\overline{x}_{m})\right\|_{C}.\end{array}

So AfA_{f} is cc -Picard operator with c=11LAf,c=\frac{1}{1-L_{A_{f}}}, where LAf=Lf(bt0)i=1maibiebit0.L_{A_{f}}=L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}.

In what follows, we consider the following operator

Bf:C([t0h,b],Rm)C([t0h,b],Rm)B_{f}:C([t_{0}-h,b],R^{m})\rightarrow C([t_{0}-h,b],R^{m})

given by

Bf(x)=(Bf1(x1,,xm),,Bfm(x1,,xm)),B_{f}(x)=(B_{f_{1}}(x_{1},\ldots,x_{m}),\ldots,B_{f_{m}}(x_{1},\ldots,x_{m})),

where

Bfi(x1,,xm)(t):={xi(t),t[t0h,t0],xi(t0)ebi(tt0)+ait0tebi(st)fi(x1(sh),,xm(sh))ds,t[t0,b].B_{f_{i}}(x_{1},\ldots,x_{m})(t):=\left\{\begin{array}[c]{l}x_{i}(t),\ t\in[t_{0}-h,t_{0}],\\ x_{i}(t_{0})e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\cdot\\ \ \ \cdot f_{i}(x_{1}(s-h),\ldots,x_{m}(s-h))ds,t\in[t_{0},b].\end{array}\right.
Theorem 6.

In the condition of Theorem 5, Bf:C([t0h,b],Rm)C([t0h,b],Rm)B_{f}:C([t_{0}-h,b],R^{m})\rightarrow C([t_{0}-h,b],R^{m}) is WPO.

Proof.

The operator BfB_{f} is a continuous operator but it is not a contraction. Let take the following notation:

Xφi:={xiC([t0h,b],R)|xi|[t0h,t0]=φi,i=1,m¯}.X_{\varphi_{i}}:=\{x_{i}\in C([t_{0}-h,b],R)|\ x_{i}|_{[t_{0}-h,t_{0}]}=\varphi_{i},\ i=\overline{1,m}\}.

Then we can write

(6) C([t0h,b],Rm)=φiC([t0h,t0],R)Xφ1××Xφm,i=1,m¯.C([t_{0}\!-\!h,b],R^{m})\!=\underset{\varphi_{i}\in C([t_{0}-h,t_{0}],R)}{\bigcup}\!X_{\varphi_{1}}\times\!\ldots\!\times X_{\varphi_{m}},\ i=\overline{1,m}.

We have that Xφ1××XφmI(Bf)X_{\varphi_{1}}\times\!\ldots\!\times X_{\varphi_{m}}\in I(B_{f}) and Bf|Xφ1××XφmB_{f}|_{X_{\varphi_{1}}\times\ldots\times X_{\varphi_{m}}} is a Picard operator, because it is the operator which appears in the proof of the Theorem 5. By applying the Theorem 2, we obtain that BfB_{f} is WPO. ∎

4. Increasing solutions of the system (2)

4.1. Inequalities of Čaplygin type

Theorem 7.

We suppose that

  1. (a)

    the conditions of the Theorem 5 are satisfied;

  2. (b)

    ui,viR,uivi,i=1,m¯u_{i},v_{i}\in R,\ u_{i}\leq v_{i},\ i=\overline{1,m}\ implies that

    fi(u1,,um)fi(v1,,vm),i=1,m¯.f_{i}(u_{1},\ldots,u_{m})\leq f_{i}(v_{1},\ldots,v_{m}),i=\overline{1,m}.

Let (x1,,xm)(x_{1},\ldots,x_{m}) be a solution of the system (2) and (y1,,ym)(y_{1},\ldots,y_{m}) a solution of the inequality system

yi(t)aifi(y1(th),,ym(th))biyi(t),t[t0,b].y_{i}^{\prime}(t)\leq a_{i}f_{i}(y_{1}(t-h),\ldots,y_{m}(t-h))-b_{i}y_{i}(t),\ t\in[t_{0},b].

Then yi(t)xi(t),t[t0h,t0],i=1,m¯y_{i}(t)\leq x_{i}(t),\ t\in[t_{0}-h,t_{0}],\ i=\overline{1,m} implies that (y1,,ym)(x1,,xm).(y_{1},\ldots,y_{m})\leq(x_{1},\ldots,x_{m}).

Proof.

In the terms of the operator BfB_{f}, we have

(x1,,xm)=Bf(x1,,xm) and (y1,,ym)Bf(y1,,ym).(\!x_{1},\!\ldots\!,x_{m}\!)\!=\!B_{f}(\!x_{1},\!\ldots\!,x_{m}\!)\text{ and }(y_{1},\!\ldots\!,y_{m})\!\leq\!B_{f}(\!y_{1},\!\ldots\!,y_{m}\!)\text{.}

However, from the condition (b), we have that BfB_{f}^{\infty} is increasing,

(y1,,ym)\displaystyle(\!y_{1},\!\ldots\!,y_{m}\!)\! Bf(y1,,ym)=Bf(y~1|[t0h,t0],,y~m|[t0h,t0])\displaystyle\!\leq B_{f}^{\infty}(\!y_{1},\!\ldots\!,y_{m}\!)\!=\!B_{f}^{\infty}(\!\widetilde{y}_{1}|_{[t_{0}\!-\!h,t_{0}]},\!\ldots\!,\widetilde{y}_{m}|_{[t_{0}\!-\!h,t_{0}]}\!)\!\leq
Bf(x~1|[t0h,t0],,x~m|[t0h,t0])=(x1,,xm).\displaystyle\leq B_{f}^{\infty}(\!\widetilde{x}_{1}|_{[t_{0}\!-\!h,t_{0}]},\!\ldots\!,\widetilde{x}_{m}|_{[t_{0}\!-\!h,t_{0}]}\!)\!=\!(x_{1},\!\ldots\!,x_{m}).

Thus (y1,,ym)(x1,,xm).(y_{1},\ldots,y_{m})\leq(x_{1},\ldots,x_{m}).

Here, we use the notation x~iXxi|[t0h,t0],i=1,m¯.\widetilde{x}_{i}\in X_{x_{i}|_{[t_{0}-h,t_{0}]}},i=\overline{1,m}.

4.2. Comparison theorem

In what follows we want to study the monotony of the solution of the problem (2)–(3), with respect to φi\varphi_{i} and fi,i=1,m¯.f_{i},\ i=\overline{1,m}. We shall use the result below:

Lemma 1.

(Abstract comparison Lemma). Let (X,d,)(X,d,\leq) be an ordered metric space and A,B,C:XXA,B,C:X\rightarrow X be such that:

  1. (i)

    ABC;A\leq B\leq C;

  2. (ii)

    the operators A,B,CA,B,C are WPO;

  3. (iii)

    the operator BB is increasing

Then xyzA(x)B(y)C(z).x\leq y\leq z\Rightarrow A^{\infty}(x)\leq B^{\infty}(y)\leq C^{\infty}(z).

In this case we can establish the theorem.

Theorem 8.

Let fijC(Rm,R),i=1,m¯,j=1,2,3.f_{i}^{j}\in C(R^{m},R),\ i=\overline{1,m},\ j=1,2,3.

We suppose that

  1. (a)

    fi2(,,):RmRf_{i}^{2}(\cdot,\ldots,\cdot):R^{m}\rightarrow R is increasing, i=1,m¯i=\overline{1,m};

  2. (b)

    fi1fi2fi3,i=1,m¯.f_{i}^{1}\leq f_{i}^{2}\leq f_{i}^{3},\ i=\overline{1,m}.

Let xj=(x1j,xmj)x^{j}=(x_{1}^{j},\ldots x_{m}^{j}) be a solution of the equation

xi(t)=aifij(x1(th),,xm(th))bixi(t),x_{i}^{\prime}(t)\!=\!a_{i}f_{i}^{j}(x_{1}(t-h),\ldots,x_{m}(t-h))-b_{i}x_{i}(t),

where t[t0,b],i=1,m¯,j=1,2,3.\ t\in[t_{0},b],i=\overline{1,m},\ j=1,2,3.

If xi1(t)xi2(t)xi3(t),t[t0h,t0],x_{i}^{1}(t)\leq x_{i}^{2}(t)\leq x_{i}^{3}(t),\ t\in[t_{0}-h,t_{0}], then xi1xi2xi3,i=1,m¯.x_{i}^{1}\leq x_{i}^{2}\leq x_{i}^{3},\ i=\overline{1,m}.

Proof.

From Theorem 5, the operators Bfj,j=1,2,3B_{f}^{j},\ j=1,2,3 are weakly Picard operators.

Taking into consideration the condition (a), the operator Bf2B_{f}^{2} is increasing.

From (b) we have that Bf1Bf2Bf3B_{f}^{1}\leq B_{f}^{2}\leq B_{f}^{3}.

We note that (x1j,,xmj)=Bfj(x~1j,,x~mj),j=1,2,3(x_{1}^{j},\ldots,x_{m}^{j})=B_{f}^{j\infty}(\widetilde{x}_{1}^{j},\ldots,\widetilde{x}_{m}^{j}),\ j=1,2,3. Now using the abstract comparison lemma, the proof is complete. ∎

5. Data dependence: continuity

Consider the Cauchy problem (2)–(3) and suppose the conditions of the Theorem 5 are satisfied. Denote by x(,φ,f)=(x1(;φ1,f1),,xm(;φm,fm)),x(\cdot,\varphi,f)=(x_{1}(\cdot;\varphi_{1},f_{1}),\ldots,x_{m}(\cdot;\varphi_{m},f_{m})),\ the solution of this problem. We can state the following result:

Theorem 9.

Let φij,fij,i=1,m¯,j=1,2\varphi_{i}^{j},f_{i}^{j},i=\overline{1,m},\ j=1,2 be as in the Theorem 5. Furthermore, we suppose that there exists ηi1,ηi2,i=1,m¯\eta_{i}^{1},\eta_{i}^{2},i=\overline{1,m} such that

  1. (i)

    |φi1(t)φi2(t)|ηi1,t[t0h,t0],\left|\varphi_{i}^{1}(t)-\varphi_{i}^{2}(t)\right|\leq\eta_{i}^{1},\ \forall t\in[t_{0}-h,t_{0}], i=1,m¯;i=\overline{1,m};

  2. (ii)

    |fi1(u1,,um)fi2(u1,,um)|ηi2,i=1,m¯,uiR.\left|f_{i}^{1}(u_{1},\ldots,u_{m})-f_{i}^{2}(u_{1},\ldots,u_{m})\right|\leq\eta_{i}^{2},\ i=\overline{1,m},\ u_{i}\in R.

Then

|xi(t;φi1,fi1)xi(t;φi2,fi2)|i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi21Lf(bt0)i=1maibiebit0,\left|x_{i}(t;\varphi_{i}^{1},f_{i}^{1})-x_{i}(\!t;\!\varphi_{i}^{2},f_{i}^{2})\right|\leq\frac{\displaystyle\sum\limits_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}(t-t_{0})}+(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{\!-b_{i}t_{0}}\eta_{i}^{2}}{1\!-\!L_{f}(b\!-\!t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{\!-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2),i=1,m¯.L_{f}=\max(L_{f^{1}},L_{f^{2}}),i=\overline{1,m}.

Proof.

Consider the operators Aφij,fij,i=1,m¯,j=1,2.A_{\varphi_{i}^{j},f_{i}^{j}},i=\overline{1,m},j=1,2. From Theorem 5 these operators are contractions.

Additionally

Aφi1,fi1(x1,,xm)Aφi2,fi2(x1,,xm)C\displaystyle\left\|A_{\varphi_{i}^{1},f_{i}^{1}}(x_{1},\ldots,x_{m})-A_{\varphi_{i}^{2},f_{i}^{2}}(x_{1},\ldots,x_{m})\right\|_{C}\leq
i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi2,\displaystyle\leq\sum\limits_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}(t-t_{0})}+(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}^{2},

x=(x1,,xm)C([t0h,b],Rm).\forall x=(x_{1},\ldots,x_{m})\in C([t_{0}-h,b],R^{m}).

Now the proof follows from the Theorem 1, with A:=Aφi1,fi1,B=Aφi2,fi2,η=i=1mηi1ebi(tt0)+(bt0)i=1maibiebit0ηi2A:=A_{\varphi_{i}^{1},f_{i}^{1}},\ B=A_{\varphi_{i}^{2},f_{i}^{2}},\ \eta=\sum\limits_{i=1}^{m}\eta_{i}^{1}e^{-b_{i}(t-t_{0})}+(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{\!-b_{i}t_{0}}\!\eta_{i}^{2} and α:=LAf=Lf(bt0)i=1maibiebit0\alpha:=L_{A_{f}}=L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}} where Lf=max(Lf1,Lf2),i=1,m¯.L_{f}=\max(L_{f^{1}},L_{f^{2}}),i=\overline{1,m}.

From the Theorem above we have:

Theorem 10.

Let fi1f_{i}^{1} and fi2f_{i}^{2} be as in the Theorem 5, i=1,m¯i=\overline{1,m}. Let SBfi1,SBfi2S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}} be the solution set of system (2) corresponding to fi1f_{i}^{1} and fi2,i=1,m¯f_{i}^{2},i=\overline{1,m}. Suppose that there exists ηi>0,i=1,m¯\eta_{i}>0,i=\overline{1,m} such that

(7) |fi1(u1,,um)fi2(u1,,um)|ηi\left|f_{i}^{1}(u_{1},\ldots,u_{m})-f_{i}^{2}(u_{1},\ldots,u_{m})\right|\leq\eta_{i}

for all uiR,i=1,m¯.u_{i}\in R,i=\overline{1,m}.

Then

HC(SBfi1,SBfi2)(bt0)i=1maibiebit0ηi1Lf(bt0)i=1maibiebit0,H_{\left\|\cdot\right\|_{C}}(S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}})\leq\frac{(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}}{1-L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2)L_{f}=\max(L_{f^{1}},L_{f^{2}}) and HCH_{\left\|\cdot\right\|_{C}} denotes the Pompeiu-Housdorff functional with respect to C\left\|\cdot\right\|_{C} on C([t0h,b],Rm).C([t_{0}-h,b],R^{m}).

Proof.

In condition of the Theorem 5, the operators Bfi1B_{f_{i}^{1}} and Bfi2,i=1,m¯B_{f_{i}^{2}},i=\overline{1,m} are c1c_{1}-WPO and c2c_{2}-weakly Picard operators.

Let

Xφi:={xiC([t0h,b],R)|xi|[t0τ1,t0]=φi,i=1,m¯}.X_{\varphi_{i}}:=\{x_{i}\in C([t_{0}-h,b],R)|\ x_{i}|_{[t_{0}-\tau_{1},t_{0}]}=\varphi_{i},i=\overline{1,m}\}.

It is clear that Bfi1|Xφi=Afi1,Bfi2|Xφi=Afi2.B_{f_{i}^{1}}|_{X_{\varphi_{i}}}=A_{f_{i}^{1}},\ B_{f_{i}^{2}}|_{X_{\varphi_{i}}}=A_{f_{i}^{2}}. So, from Theorem 2 and Theorem 5 we have

Bfi12(x1,,xm)Bfi1(x1,,xm)CLf1(bt0)i=1maibiebit0Bfi1(x1,,xm)(x1,,xm)C,\begin{array}[c]{l}\left\|B_{f_{i}^{1}}^{2}(x_{1},\ldots,x_{m})-B_{f_{i}^{1}}(x_{1},\ldots,x_{m})\right\|_{C}\leq\\ \leq L_{f^{1}}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|B_{f_{i}^{1}}(x_{1},\ldots,x_{m})-(x_{1},\ldots,x_{m})\right\|_{C},\end{array}
Bfi22(x1,,xm)Bfi2(x1,,xm)CLf2(bt0)i=1maibiebit0Bfi2(x1,,xm)(x1,,xm)C,\begin{array}[c]{l}\left\|B_{f_{i}^{2}}^{2}(x_{1},\ldots,x_{m})-B_{f_{i}^{2}}(x_{1},\ldots,x_{m})\right\|_{C}\leq\\ \leq L_{f^{2}}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\left\|B_{f_{i}^{2}}(x_{1},\ldots,x_{m})-(x_{1},\ldots,x_{m})\right\|_{C},\end{array}

for all (x1,,xm)C([t0h,b],Rm),i=1,m¯.(x_{1},\ldots,x_{m})\in C([t_{0}-h,b],R^{m}),i=\overline{1,m}.

Now, choosing

α1\displaystyle\alpha_{1} =Lf1(bt0)i=1maibiebit0and\displaystyle=L_{f^{1}}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\ \text{and}
α2\displaystyle\alpha_{2} =Lf2(bt0)i=1maibiebit0,\displaystyle=L_{f^{2}}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}},

we get that Bfi1B_{f_{i}^{1}} and Bfi2B_{f_{i}^{2}} are c1c_{1}-weakly Picard operators and c2c_{2}-weakly Picard operators with c1=(1α1)1c_{1}=(1-\alpha_{1})^{-1}\ and c2=(1α2)1\ c_{2}=(1-\alpha_{2})^{-1}. From (7) we obtain that

Bfi1(x1,,xm)Bfi2(x1,,xm)C(bt0)i=1maibiebit0ηi,\left\|B_{f_{i}^{1}}(x_{1},\ldots,x_{m})-B_{f_{i}^{2}}(x_{1},\ldots,x_{m})\right\|_{C}\leq(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i},

(x1,,xm)C([t0h,b],Rm),i=1,m¯.\forall(x_{1},\ldots,x_{m})\in C([t_{0}-h,b],R^{m}),i=\overline{1,m}. Applying Theorem 3 we have that

HC(SBfi1,SBfi2)(bt0)i=1maibiebit0ηi1Lf(bt0)i=1maibiebit0,H_{\left\|\cdot\right\|_{C}}(S_{B_{f_{i}^{1}}},S_{B_{f_{i}^{2}}})\leq\frac{(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}\eta_{i}}{1-L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}},

where Lf=max(Lf1,Lf2)L_{f}=\max(L_{f^{1}},L_{f^{2}}) and HCH_{\left\|\cdot\right\|_{C}} is the Pompeiu-Housdorff functional with respect to C\left\|\cdot\right\|_{C} on C([t0h,b],Rm).C([t_{0}-h,b],R^{m}).

6. Data dependence: differentiability

Consider the following differential system with parameter

(8) xi(t)=aifi(x1(th),,xm(th);λ)bixi(t),t[t0,b],i=1,m¯,x_{i}^{\prime}(t)=a_{i}f_{i}(x_{1}(t-h),\ldots,x_{m}(t-h);\lambda)-b_{i}x_{i}(t),t\in[t_{0},b],i=\overline{1,m},
(9) xi(t)=φi(t),t[t0h,t0],i=1,m¯.x_{i}(t)=\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}],i=\overline{1,m}.

Suppose that we have satisfied the following conditions:

  1. (C1)

    t0<b,h>0,JRt_{0}<b,h>0,\ J\subset R a compact interval;

  2. (C2)

    fiC1(Rm×J,R),i=1,m¯;f_{i}\in C^{1}(R^{m}\times J,R),\ i=\overline{1,m};

  3. (C3)

    φiC([t0h,t0],R),i=1,m¯;\varphi_{i}\in C([t_{0}-h,t_{0}],R),\ i=\overline{1,m};

  4. (C4)

    there exists Lf>0,i=1,m¯L_{f}>0,\ i=\overline{1,m} such that

    |fi(u1,,um;λ)ui|Lf,uiR,i=1,m¯,λJ;\left|\frac{\partial f_{i}(u_{1},\ldots,u_{m};\lambda)}{\partial u_{i}}\right|\leq L_{f},u_{i}\in R,\ i=\overline{1,m},\lambda\in J;
  5. (C5)

    Lf(bt0)i=1maibiebit0<1.L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}<1.

Then, from Theorem 5, we have that the problem (2)–(3) has a unique solution, (x1(,λ),,xm(,λ)).(x_{1}^{\ast}(\cdot,\lambda),\ldots,x_{m}^{\ast}(\cdot,\lambda)).

We prove that xi(,λ)C1(J),  t[t0h,b],i=1,m¯.x_{i}^{\ast}(\cdot,\lambda)\in C^{1}(J),\text{ }\forall\text{ }t\in[t_{0}\!-\!h,b],i=\overline{1,m}.

For this we consider the system

(10) xi(t,λ)=aifi(x1(th;λ),,xm(th;λ);λ)bixi(t;λ),x_{i}^{\prime}(t,\lambda)=a_{i}f_{i}(x_{1}(t-h;\lambda),\ldots,x_{m}(t-h;\lambda);\lambda)-b_{i}x_{i}(t;\lambda),

t[t0,b],λJ,xiC([t0h,b]×J,R)C1([t0,b]×J,R),i=1,m¯.t\in[t_{0},b],\ \lambda\in J,\ x_{i}\in C([t_{0}-h,b]\times J,R)\cap C^{1}([t_{0},b]\times J,R),\ i=\overline{1,m}.

Theorem 11.

Consider the problem (10)–(9), and suppose the conditions (C1{}_{\text{1}})–(C5{}_{\text{5}}) hold. Then,

  1. (i)

    (10)–(9) has a unique solution (x1(,λ),,xm(,λ))(x_{1}^{\ast}(\cdot,\lambda),\ldots,x_{m}^{\ast}(\cdot,\lambda)), in C([t0h,b]×J,Rm);C([t_{0}-h,b]\times J,R^{m});

  2. (ii)

    (x1(,λ),,xm(,λ))C1(J),(x_{1}^{\ast}(\cdot,\lambda),\ldots,x_{m}^{\ast}(\cdot,\lambda))\in C^{1}(J), t[t0h,b],i=1,m¯.\forall t\in[t_{0}-h,b],i=\overline{1,m}.

Proof.

The problem (10)–(9) is equivalent with the following functional-integral equation

(11) xi(t;λ)={φi(t),t[t0h,t0]φi(t)ebi(tt0)+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ),t[t0,b].x_{i}(t;\lambda)=\left\{\!\begin{array}[c]{l}\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}]\\ \varphi_{i}(t)e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}f_{i}(x_{1}(s-h;\lambda),\ldots,\\ \ \ x_{m}(s-h;\lambda);\lambda),t\in[t_{0},b].\end{array}\right.

Now let take the operator

A:C([t0h,b]×J,Rm)C([t0h,b]×J,Rm),A:C([t_{0}-h,b]\times J,R^{m})\rightarrow C([t_{0}-h,b]\times J,R^{m}),

given by

A(x1,,xm)=(A1(x1,,xm),,Am(x1,,xm)),A(x_{1},\ldots,x_{m})=(A_{1}(x_{1},\ldots,x_{m}),\ldots,A_{m}(x_{1},\ldots,x_{m})),

where

Ai(x1,,xm)(t;λ):={φi(t),t[t0h,t0]φi(t)ebi(tt0)+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ),t[t0,b]A_{i}(x_{1},\ldots,x_{m})(t;\lambda):=\left\{\!\begin{array}[c]{l}\varphi_{i}(t),\ t\in[t_{0}-h,t_{0}]\\ \varphi_{i}(t)e^{-b_{i}(t-t_{0})}+a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\cdot\\ \ \ \cdot f_{i}(x_{1}(s-h;\lambda),\ldots,x_{m}(s-h;\lambda);\lambda),t\!\in\![t_{0},b]\end{array}\right.

Let X=C([t0τ1,b]×J,Rm).X=C([t_{0}-\tau_{1},b]\times J,R^{m}).

It is clear, from the proof of the Theorem 5, that in the condition (C1{}_{\text{1}})–(C5{}_{\text{5}}), the operatorA:(X,C)(X,C)A:(X,\left\|\cdot\right\|_{C})\rightarrow(X,\left\|\cdot\right\|_{C}) is Picard operator.

Let (x1,,xm)(x_{1}^{\ast},\ldots,x_{m}^{\ast}) be the unique fixed point of A.A.

Supposing that there exists xiλ,i=1,m¯\dfrac{\partial x_{i}^{\ast}}{\partial\lambda},\ i=\overline{1,m}, from (11), we have that

xiλ\displaystyle\dfrac{\partial x_{i}^{\ast}}{\partial\lambda} =ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)u1x1(sh,λ)λ𝑑s+\displaystyle\!\!=\!a_{i}\int_{t_{0}}^{t}e^{b_{i}(s\!-\!t)}\frac{\partial f_{i}(x_{1}^{\ast}(s\!-\!h;\lambda),\!\ldots\!,x_{m}^{\ast}(s\!-\!h;\lambda);\lambda)}{\partial u_{1}}\cdot\frac{\partial x_{1}^{\ast}(s-h,\lambda)}{\partial\lambda}ds+\ldots
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)umxm(sh,λ)λ𝑑s+\displaystyle\ \ \ +\!a_{i}\!\int_{t_{0}}^{t}\!e^{b_{i}(s\!-\!t)}\frac{\partial f_{i}(x_{1}^{\ast}(s\!-\!h;\lambda),\!\ldots\!,x_{m}^{\ast}(s\!-\!h;\lambda);\lambda)}{\partial u_{m}}\cdot\frac{\partial x_{m}^{\ast}(s-h,\lambda)}{\partial\lambda}ds+
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)λ𝑑s,\displaystyle\ \ \ +a_{i}\!\int_{t_{0}}^{t}e^{b_{i}(s\!-\!t)}\!\frac{\partial f_{i}(x_{1}^{\ast}(s\!-\!h;\lambda),\!\ldots\!,x_{m}^{\ast}(s\!-\!h;\lambda);\lambda)}{\partial\lambda}ds,

for all t[t0,b],λJ,i=1,m¯.t\in[t_{0},b],\lambda\in J,i=\overline{1,m}.

This relation suggest us to consider the following operator

C\displaystyle C :X×XX,\displaystyle:X\times X\rightarrow X,
(x1,,xm,u1,,um)\displaystyle(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}) C(x1,,xm,u1,,um),\displaystyle\rightarrow C(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m}),

where Ci(x1,,xm,u1,,um)(t;λ)=0C_{i}(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m})(t;\lambda)\!=0 for t[t0h,t0],λJ,i=1,m¯t\in[t_{0}-h,t_{0}],\lambda\in J,i=\overline{1,m} and

Ci(x1,,xm,u1,,um)(t;λ):=\displaystyle C_{i}(x_{1},\ldots,x_{m},u_{1},\ldots,u_{m})(t;\lambda):=
=ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)u1u1(sh;λ)𝑑s+\displaystyle=a_{i}\int_{t_{0}}^{t}e^{b_{i}(s-t)}\frac{\partial f_{i}(x_{1}^{\ast}(s-h;\lambda),\ldots,x_{m}^{\ast}(s-h;\lambda);\lambda)}{\partial u_{1}}\cdot u_{1}(s-h;\lambda)ds+\ldots
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)umum(sh;λ)𝑑s+\displaystyle\ \ \ +a_{i}\int_{t_{0}}^{t}e^{b_{i}(s\!-\!t)}\frac{\partial f_{i}(x_{1}^{\ast}(s\!-\!h;\lambda),\!\ldots\!,x_{m}^{\ast}(s\!-\!h;\lambda);\lambda)}{\partial u_{m}}\cdot u_{m}(s-h;\lambda)ds+
+ait0tebi(st)fi(x1(sh;λ),,xm(sh;λ);λ)λ𝑑s,\displaystyle\ \ \ +a_{i}\int_{t_{0}}^{t}e^{b_{i}(s\!-\!t)}\frac{\partial f_{i}(x_{1}^{\ast}(s\!-\!h;\lambda),\!\ldots\!,x_{m}^{\ast}(s\!-\!h;\lambda);\lambda)}{\partial\lambda}ds,

for t[t0,b],λJ,i=1,m¯.t\in[t_{0},b],\lambda\in J,i=\overline{1,m}.

In this way we have the triangular operator

D:X×XX×X,\displaystyle D:X\times X\rightarrow X\times X,
(x1,,xm,u1,,um)(A(x1,,xm),C(x1,,xm,u1,,um)),\displaystyle(x_{1},\!\ldots\!,x_{m},u_{1},\!\ldots\!,u_{m})\rightarrow(A(x_{1},\!\ldots\!,x_{m}),C(x_{1},\!\ldots\!,x_{m},u_{1},\!\ldots\!,u_{m})),

where AA is Picard operator and C(x1,,xm,,,):YYC(x_{1},\!\ldots\!,x_{m},\cdot,\!\ldots\!,\cdot):Y\rightarrow Y is LCL_{C} -contraction with LC=Lf(bt0)i=1maibiebit0L_{C}=L_{f}(b-t_{0}){\displaystyle\sum\limits_{i=1}^{m}}\frac{a_{i}}{b_{i}}e^{-b_{i}t_{0}}.

From Theorem 4 we have that the operator DD is Picard operator, i.e. the sequences

(x1,n+1,,xm,n+1)\displaystyle(x_{1,n+1},\ldots,x_{m,n+1})\! :=A(x1,n,,xm,n),\displaystyle:=\!A(x_{1,n},\ldots,x_{m,n}),
(u1,n+1,,um,n+1)\displaystyle(u_{1,n+1},\ldots,u_{m,n+1})\! :=C(x1,n,,xm,n,u1,n,,um,n),\displaystyle:=\!C(x_{1,n},\ldots,x_{m,n},u_{1,n},\ldots,u_{m,n}),

nNn\in N, converges uniformly, with respect to tX,λJ,t\in X,\ \lambda\in J, to (x1,,xm,u1,,um)FD(x_{1}^{\ast},\!\ldots\!,x_{m}^{\ast},u_{1}^{\ast},\!\ldots\!,u_{m}^{\ast})\\ \in F_{D}, for all (x1,0,,xm,0)X,(u1,0,,um,0)X(x_{1,0},\ldots,x_{m,0})\in X,\ (u_{1,0},\ldots,u_{m,0})\in X.

If we take

x1,0=0,,xm,0=0,x_{1,0}=0,\ldots,\;x_{m,0}=0,
u1,0=x1,0λ=0,,um,0=xm,0λ=0,u_{1,0}=\dfrac{\partial x_{1,0}}{\partial\lambda}=0,\ldots,u_{m,0}=\dfrac{\partial x_{m,0}}{\partial\lambda}=0,

then

u1,1=x1,1λ,,um,1=xm,1λ.u_{1,1}=\frac{\partial x_{1,1}}{\partial\lambda},\ldots,u_{m,1}=\frac{\partial x_{m,1}}{\partial\lambda}.

By induction we prove that

u1,n=x1,nλ,,um,n=xm,nλ,nN.\displaystyle u_{1,n}=\frac{\partial x_{1,n}}{\partial\lambda},\cdots,u_{m,n}=\frac{\partial x_{m,n}}{\partial\lambda},\;\forall n\in N.

So

x1,nunifx1,,xm,nunifxm, as n,\displaystyle x_{1,n}\overset{unif}{\rightarrow}x_{1}^{\ast},\cdots,x_{m,n}\overset{unif}{\rightarrow}x_{m}^{\ast},\text{ as }n\rightarrow\infty,
x1,nλunifu1,,xm,nλunifum, as n.\displaystyle\frac{\partial x_{1,n}}{\partial\lambda}\overset{unif}{\rightarrow}u_{1}^{\ast},\cdots,\frac{\partial x_{m,n}}{\partial\lambda}\overset{unif}{\rightarrow}u_{m}^{\ast},\text{ as }n\rightarrow\infty.

From a Weierstrass argument we have that there exists xiλ,i=1,m¯\dfrac{\partial x_{i}^{\ast}}{\partial\lambda},\;i=\overline{1,m} and

x1λ=u1,,xmλ=um.\frac{\partial x_{1}^{\ast}}{\partial\lambda}=u_{1}^{\ast},\ldots,\frac{\partial x_{m}^{\ast}}{\partial\lambda}=u_{m}^{\ast}\text{.}

References

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2008

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