[1] H. Brunner, The approximate solution of initial-value problems fr Volterra integro-differential equations, Computing 40 (1988, pp. 125-137.
[2] H. Brunner, The numerical solution of initial-values problems for integro-differential equations, Nurmerical Analysis (1988), pp. 18-38.
[3] H. Brunner and P. J. van der Houwen, The numerical solution of Volterra equations, CWI Monographs, Vol. 3, North-Holland, Armsterdam-New York, 1986.
[4] I.Danciu, The numerical of nonlinear Volterra integral equations of the second king by the exact collocation method, Revue d’Analyse Numérique et de Théorie de l’Approximation, 24, 1-2 (1995) pp. 59-73.
[5] I. Danciu, the numerical treatment of nonlinear Volterra integral equations of the second kind by the discretized collocatgion method, Revue d’analyse Numérique et de Théorie de l’Approximation, 24, 1-2 (1995), pp. 75-89.
[6] G. Micula, Funcţii spline şi aplicaţii, Ed. Tehnică, Bucureşti, 1978.
[7] M. Micula and G. Micula, Sur la résolution numérique des équations intégrales du type Volterra de second espièce à l’aide de fonction splines, Studia, Babeş-Bolyai Math. 18 (1973), pp. 65-68.
Paper (preprint) in HTML form
POLYNOMIAL SPLINE COLLOCATION METHODS FOR VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS
I. DANCIU
(Cluj-Napoca)
1. INTRODUCTION
Consider the first-order Volterra integro-differential equation (VIDE):
(1.1)
with initial condition . Here, the given functions and (with ), are supposed to be sufficiently smooth for the initial-value problem for VIDE (1.1) to have a unique solution , with (see[3], [6]).
VIDE-s of the above form will be solved numerically in certain polynomial spline spaces. In order to describe these approximating spaces let (with ) be a mesh for the given interval . and set
Moreover, let denote the space of (real) polynomials of degree not exceeding . We then define, for given integers and with and ,
to be the space of polynomial splines of degree whose elements possess the knots and are times continually differentiable on . If , then the elements of may have jump discontinues at the knots .
In many papers, the problem of approximating the exact solution of initialvalue problem for , has been solved by collocation method in polynomial splines spaces and (see [1], [2], [3]) or in polynomial splines space (see[6]). In this paper we shall construct an approximate solution in the space of polynomial spline functions , with and . This approximation will be determined by collocation methods. The attainable order of global and local convergence of these methods is analyzed in detail.
2. COLLOCATION IN POLYNOMIAL SPLINE SPACES
We shall assume in the following that mesh sequence is quasiuniform, that is, there exists a finite constant independent of such that:
In [7] M. Micula and G. Micula proved that an element has for all and for all the following form:
(2.1)
where:
From (2.1) we have that on element is well defined when we know the coefficients for all . In order to determine these coefficients we consider the set of collocation parameters , where , and we define the set of collocation points by:
(2.2)
The approximate solution will be determined imposing the condition that satisfy the on and the initial condition, i.e.:
(2.3) , for all , with . The exact collocation equation (2.3) may be written in the form:
(2.4)
where:
denotes the lag term.
For small enought it is easy to show that system (2.4) has a unique solution for all .
For linear the version of (1.1)
(2.5)
the collocation equation assumes the form:
(2.6)
where:
We phrase our convergence results for the linear equation (2.6); a remark on the extension of these results to the general case (1.1) will follow each of the proofs.
In most applications the integrals (2.7) occurring in the exact collocation (2.6) cannot be evaluated analytically, and one is forced to resort to employing suitable quadrature formulas for their approximation. In the following we suppose that these integrals are approximated by quadrature formulas of the form:
(2.8) where and are two given positive integers; are two sets of parameters satisfying, respectively:
and denote the quadrature weights.
The corresponding error term are defined by:
(2.9)
Hence, the fully discretization version of the collocation equation (2.6) is given by:
(2.10)
One can observe that the approximation , given by the fully discretized collocation equations (2.10) will, in general, be different from the approximation given by the exact collocation equations (2.6). For all and for all the approximation has the form:
(2.11)
with:
Equations (2.6) and (2.10) represent, for each a recursive system which will give the unknowns , respectively . Since
this solutions have been found, the values of and together with their derivatives on are determined by the formula (2.1), respectively, by the formula (2.11).
3. GLOBAL CONVERGENCE RESULTS
If the given functions and are of class on their domain of definition, then the VIDE (2.5) has a unique solution , which is of class . For a function defined on we shall denote by the restriction of to the subinterval , for all , and we shall use the following norm:
(3.1)
Concerning the convergence of the method described above we give the following theorems:
THEOREM 3.1 Let and in (2.5) be times continuously differentiable on their respective domains and . Then, for every choice of the collocation parameters with and for all quasi-uniform mesh sequences with sufficiently small , we have:
(i) the exact collocation equation (2.6) defines a unique approximation , and the resulting error function satisfies:
(3.2)
where are finite constants independent of ;
(ii) if the quadrature formulas (2.8) satisfy:
(3.3)
and, for ,
(3.4)
whenever the integrand is a sufficiently smooth function, then for the approximation defined by the discretized collocation equation (2.10), the following relations hold:
(3.5)
and
(3.6)
where and are finite constants independent of .
Proof. We shall prove it by induction using the same technique as in [4] or in [5].
(i) For and for all the exact solution can be developed in Taylor series:
(3.7)
where:
So, by (2.1) and (3.7) we have:
(3.8)
where:
Taking into account that is a solution of (2.5) and satisfies the exact collocation equation (2.6) and employing the expression (3.8) for , we are led to:
(3.9)
where, we have introduced the abbreviations and .
Relation (3.9) can be written:
(3.10)
where denote the set of matrices with lines and columns) and are the column vectors. The explicit form of the matrices and the vectors results from (3.9).
For , by (2.1) and (3.10) we obtain:
(3.11)
From the assumptions of the theorem it results that the vector is bounded and for sufficiently small the matrix possesses a uniformly bounded inverse. Hence, for we have:
(3.12)
and from (3.8) it results:
(3.13)
Deriving relation (3.8) times and using (3.12) we obtain:
(3.14)
Suppose now that, for all
(3.15)
hold and prove that (3.15) holds for .
By (3.9), (3.10), (3.15) and the assumptions of the theorem it follows that for sufficiently small the matrix possess a uniformly bounded inverse, and is bound. Thus, from (3.10) for , we obtain:
and from (3.8) it results:
(3.17)
for all and
Evaluations (3.14), (3.15) and (3.17) end the proof of the first assertion by the theorem.
(ii) By (2.1) and (2.11) it follows that the function can be written for every , thus:
(3.18)
where:
If we now substract the discretized collocation equation (2.10) from the exact collocation equation (2.6) and we use relations (2.9) and (3.18), we are led to:
(3.19)
where , and the matrices and the vectors have the same sizes as and from (3.10), the differences between them consisting in the fact that the integrals from (3.9) are replaced with quadrature formulas of the form (2.8).
The above expression has the same structure as (3.10). From the smoothness hypothesis and from the assumptions on the order of the quadrature formulas (3.3) and (3.4) we have: and . Thus, repeating the reasoning from the proof of the assertion (i), it easily results that relation (3.5) is true.
Now by (3.2) and (3.5) it results:
for all , with .
COROLLARY 3.2 Let the assumptions of Theorem 3.1 hold. If the quadrature formulas (2.8) are of interpolatory type, with , then the approximation defined by the discretized collocation equation (2.10) leads to an error satisfying:
(3.20)
for , and for every choice of the collocation parameters with .
In many papers (see [1], [2], [3]) the quadrature formulas used have , and . The possibility of employing some quadrature formulas of the this type in our method would lead to some simplifications. These simplifications are useful when they do not spoil the convergence order given by Theorem 3.1 (i), namely . An answer to this problem is given in the following corollary.
COROLLARY 3.3. If in VIDE (2.5), and and if , then there exists the set of collocation parameters such that for the approximation given by the discrete collocation equations (2.10) in which and we have:
(3.21)
for as with .
Proof. If and then we choose the set of collocation parameters to be formed by the Gauss points for .
Remark 3.4. (i) The results of the above theorems for and are similar to the results given in [3], while for and they are similar to the result from [6].
(ii) The extension of the above arguments to nonlinear VIDE (1.1) is straightforward: in the error equations (3.10) and (3.19), the roles of and of are taken, respectively, by and , with and denoting suitable intermediate values arising in the application of the Mean-Value Theorem (see [3], [5]).
4.LOCAL SUPERCONVERGENCE ON
The notion of local superconvergence is used when on a set of interior points (or ), the approximate solution has a convergence order greater than the global convergence order. From Theorem 3.1 we notice that the only conditions imposed on the collocation parameters are that they must be distinct and
they must belong to . The local superconvergence on is closely connected with the choice of the collocation parameters (see [3], [4], [5]) and with the relation between their number and the number of the coefficients of the approximate solution determined from the smooth conditions.
We will give the following theorem concerning the aspects presented above:
THEOREM 4.1. Suppose that:
(I) the given functions and from VIDE (2.5) are times continuously differentiable on their respective domains and (where );
(II) ;
(III) the collocation parameters , with are chosen such that:
(4.1)
Then, for all quasi-uniform mesh sequences with sufficiently small , we have:
(i) if is the approximate solution defined by the exact collocation equation (2.6) and is the exact solution of VIDE (2.5) then:
(4.2)
(ii) if the quadrature formulas (2.8) satisfy (3.3) and is the approximate solution defined by the discretized collocation equation (2.10) then:
(4.3)
where ;
(iii) if and the collocation parameters , are chosen such that relation (4.1) holds and , then:
and
(4.5)
where .
Proof. (i) The exact collocation equation (2.6) can be written in the form:
(4.6)
where denotes a suitable function, subsequently called the defect function, vanishing on .
By (4.6) and (2.5) we obtain for the error function the following VIDE:
(4.7)
The solution of (4.7) can be expressed in the form (see Theorem 1.3.4. from [3]):
(4.8)
where represents the resolvent kernel associated with the VIDE (2.5), and hence with VIDE (4.7).
If in (4.8), for , we replace each integral by the sum of the interpolatory quadrature formula with abscissas and the corresponding remainder term , since , we obtain:
(4.9)
From (4.1) we have that for for and hence from (4.9) it results , evaluation which proves the first assertion of the theorem.
(ii) The assertion of Theorem 4.1 (ii) now follows from (3.5) and (4.2). We mention that relation (4.3) can be straightly proved using the same technique as in Theorem 3.1 from [5].
(iii)By (4.8) we obtain:
(4.10)
since (see T 1.3.4 from [3]).
For we have and by (4.10) for it results, in complete analogy to (4.9):
(4.11)
where denote the quadrature errors associated with the -point interpolatory quadrature formulas, based on the abscissas , for the integrals from (4.10). The assertions of Theorem (3.1) (iii) now follows by the arguments employed at the end of the proof of (i) and (ii).
COROLLARY 4.2. Let the assumptions of Theorem 3.1 hold. Then:
(i) for the approximation given by the discrete collocation equation (2.10) in which and we have:
and for we have:
(ii) if the collocation parameters are the zeros of (Gauss points for , then and
(iii) if the collocation parameters are the zeros of - (Radau II points for , then and
(iv) if the discretized collocation equation (2.10) is characterized by interpolatory m-point qaadrature approximations with , then the resulting approximation has the property that:
if and only if, ( ), ( ) and one of ( ), ( ), ( ) holds:
(a) the collocation parameters are the Gauss points for ;
(b) ;
(c) ;
(c’) , where the are the Radau I points for ;
(c") , where the are the Radau II points
for .
Proof. The above results are proved by H. Brunner and P. J. van der Houwen in the case (i.e (see [3], pp.279-299)). Also they hold in our case , the proofs can be identically transposed.
5. NUMERICAL EXAMPLES
The convergence results derived in the preceding sections will be illustrated by the collocation methods to the following test problem:
(5.1)
whose exact solution is , and two linear problems:
(5.2)
whose exact solution is , and
(5.3)
whose exact solution is .
For above problems we have tested the collocation methods based on:
A. set of collocation points if , and the set if ;
B. Radau II points if , and the points if
C. Gauss points if , and the points if .
The tables contain the values of approximated error in the end point, i.e. the value , the number of correct digits obtained at the end point, i.e. the value of:
and the effective order of numerical method, i.e. the value of
for various values of the .
Approximated error, number of correct significant digits and effective orders for problem (5.1), with , for and
Table 1: Table 5.1.a
A
C
1/2
1/4
1/8
1/16
Approximated error, number of correct significant digits and effective orders for problem (5.1), with , for and
Table 2: Table 5.1.b
A
C
1/ 2 1/ 4 1 / 8
3.06 3
Table 3: Table 5.1.c
Approximated error, number of correct significant digits and effective orders for problem (5.1), with , for and
C
1 / 2 1 / 8
Approximated error, number of correct significant digits and effective orders for problem (5.2), for and
Table 4: Table 5.2
C
1 / 2 1 / 4 1/8 1 / 16
Using the Maple Programing Language, the collocation method apply at the problem (5.3) in all cases from above, we yield the exact solution, i.e. for all .
Finally, from numerical examples printed in Tables 5.1 and 5.2, we can observe a good concordance between theoretical results presented in the preceding sections and corresponding results given in this section.
REFERENCES
1.
H. Brunner, The approximate solution of initial-value problems for Volterra integro-differential equations, Computing 40 (1988), pp. 125-137.
2.
H. Brunner, The mumerical solution of initial-values problems for integro-differential equations, Numerical Analysis (1988), pp. 18-38.
3.
H. Brunner and P. J. van der Houwen, The numerical solution of Volterra equations, CWI Monographs, Vol. 3, North-Holland, Amsterdam-New York, 1986.
4.
I. Danciu, The numerical treatment of nonlinear Volterra integral equations of the second kind by the exact collocation method, Revue d’Analyse Numérique et de Théorie de l’Approximation, 24 , l-2 (1995), 59-73.
5.
I. Danciu, The numerical treatment of nonlinear Volterra integral equations of the second kind by the discretized collocation method, Revue d’Analyse Numérique et de Théorie de l’Approximation, 24, 1-2 (1995), 75-89.
6.
G. Micula, Functii spline si aplicatii, Ed. Tehnică, Bucuresti, 1978.
7.
M. Micula and G. Micula, Sur la résolution mumérique des équations intégrales du type Volterra de seconde espièce à l’aide de fonction splines, Studia Univ. Babes-Bolyai Math., 18 (1973), 65-68.