Abstract
The starting point is an approximation process consisting of linear and positive operators. The purpose of this note is to establish the limit of the iterates of some multidimensional approximation operators. The main tool is a Perov’s result which represents a generalization of Banach fixed point theorem. In order to support the theoretical aspects, we present three applications targeting respectively the operators Bernstein, Cheney-Sharma and those of binomial type. The last class involves an incursion into umbral calculus.
Authors
Octavian Agratini
Department of Mathematics, Babes-Bolyai University, Cluj-Napoca, Romania
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy
Radu Precup
Institute of Advanced Studies in Science and Technology, Babes-Bolyai University, Cluj-Napoca, Romania
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy
Keywords
Linear positive operator, contraction principle, Perov theorem, Bernstein operator, CheneySharma operator, umbral calculus, binomial operator.
Paper coordinates
O. Agratini, R. Precup, Iterates of multidimensional approximation operators via Perov theorem, Carpathian J. Math., 38 (2022) no. 3, pp. 539-546, https://doi.org/10.37193/CJM.2022.03.02
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1584 – 2851
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Iterates of multidimensional approximation operators via Perov theorem
Abstract.
The starting point is an approximation process consisting of linear and positive operators. The purpose of this note is to establish the limit of the iterates of some multidimensional approximation operators. The main tool is a Perov’s result which represents a generalization of Banach fixed point theorem. In order to support the theoretical aspects, we present three applications targeting respectively the operators Bernstein, Cheney-Sharma and those of binomial type. The last class involves an incursion into umbral calculus.
Key words and phrases:
Linear positive operator, contraction principle, Perov theorem, Bernstein operator, Cheney-Sharma operator, umbral calculus, binomial operator.2020 Mathematics Subject Classification:
41A36, 47H101. Introduction
It is acknowledged that linear positive operators are a useful tool in approximation signals. Referring to classical operators of discrete or continuous type, a constant concern is to highlight their properties such as the rate of convergence for functions belonging to various spaces, preservation of the properties of functions that have been approximated, extensions in q-Calculus, replacement of the classical convergence with statistical convergence.
For a linear positive approximation process , a distinct direction of study is to investigate the convergence behavior of the sequence , where
assuming that is fixed and does not depend on .
In the following we consider that the space is endowed with the Chebyshev norm , .
Best of our knowledge, the first result was obtained in 1967 by Kelisky and Rivlin [11]. It targeted the well-known Bernstein operators
(1) |
where
The result established [11, Eq. (2.4)] is read as follows
(2) |
, saying that converges uniformly to the line segment joining to .
The above result was reobtained in 2004 by I.A. Rus [17] using another technique based on fixed point theory, more exactly on Banach contraction principle. The idea was taken over and developed in other papers, for example we mention [1], [2], [9].
The purpose of this note is to provide an approach for multidimensional operators. To achieve this, we rely on a specific generalization of the concept of metric space. Perov [13] used the notion of vector-valued metric space and obtained a Banach type fixed theorem on such a complete generalized metric space by using matrices instead of Lipschitz constants. Perov’s result have been exploited in various works, see, e.g., [3], [7], [8], [12], [15].
2. Iterates of multidimensional linear positive operators
For a wider information of the reader and the accomplishment of an independent exposition, we will briefly present the method used for the study of the limit of iterations for one-dimensional operators via fixed point theory, as, for example, it appears in [1].
Set
(3) |
Every is a closed subset of and, clearly, the system , , constitutes a partition of this space. We define the linear positive operators , , that enjoy the following properties:
(i) they reproduce the Korovkin test function and , where , , ;
(ii) each , , is a contraction allowing us to say that exists such that
(4) |
(iii)
(5) |
Since is linear, the first condition implies that it reproduces affine functions. Such operators are also called Markov type. Also, the last requirement indicates the interpolation property of the operators at the end of the domain. This condition guarantees that each is an invariant subset of the operators .
Considering the function defined on
(6) |
it is observed that . Since reproduces the affine functions, is a fixed point of . For any belonging to the space one has and, by applying the contraction principle on we deduce
uniformly on .
With these preparations and using Perov’s theorem we will extend the above result to the multidimensional case.
In the first step we consider a net on named and a system where each function belongs to . Defining
(7) |
we assume
i.e., our system is a blending one related to , . Also we suppose that conditions (4) and (5) are fulfilled. In order to construct a convex combination of such operators, let
(8) |
In the second step, let and . Define the operator
(9) |
(10) |
where is given by (3). The above combination uses operators of the form (7) having different orders, namely , . Our main result will be read as follows.
For any vector-valued function , , one has
(11) |
where is given by (9) and the components of the vector-valued function are all equal with the affine function defined by (6).
Proof.
We will use the vector version of Banach contraction principle. We only need to show that is a Perov contraction on the space . This involves proving that there is a quadratic matrix, say , of size which converges to zero (i.e. tends to the null matrix as tends to infinity) such that
(12) |
for all , where by we mean the vector-valued norm given as follows
indicating the Chebyshev norm on .
According to our hypothesis, any operator defined by (7) is a contraction on with Lipschitz constant . Taking in view relation (10), for any we get
(13) |
Noting , we have . We define the matrix as follows , where . Clearly, relation (13) yields (12).
By induction we prove
(14) |
where all entries of the matrix are equal with 1. The key relation used is (8). For we have
that is Further, assuming that and observing that we obtain that and the induction is completed.
Our statement (11) follows from Perov theorem since is the unique fixed point of the operator . ∎
3. Applications
3.1. Application 1
Let be Bernstein operator , see (1). It is known that is a Markov type operator interpolating the functions at the extremities of the domain . Moreover, is a contraction for all , where Lipschitz constant is .
For we reobtain the identity (2) which is the classical result of Kelisky and Rivlin [11, Eq. (2.4)].
Remark. At first we recall the notion of weakly Picard operator, see e.g., [21]. Let be a metric space. An operator is a weakly Picard operator (abbreviated WPO) if the sequence converges for all and the limit (which may depend on ) is a fixed point of . Set
By using this concept, Kelisky-Rivlin result can be reformulated as follows: for each , is WPO and .
Recently, following the same route of WPO, in [4], the limit of iterates of modified Bernstein operators in Durrmeyer sense has been approached.
3.2. Application 2
In our attention is a generalization of Bernstein operators, the basis of its construction being a combinatorial identity of Jensen [10]
(15) |
The inception of its motivation is Lagrange’s formula
and proceeds by setting , . Choosing in (15), Cheney and Sharma [5] have investigated the operators
(16) |
where is a non-negative parameter and
Obviously, the Bernstein polynomials represent a particular case of (16) obtained by setting .
3.3. Application 3
Here we have in mind operators constructed with the help of binomial polynomials. This involves a foray into umbral calculus, consequently at the beginning we will point out the basics. The first rigorous version of this calculus belongs to Gian-Carlo Rota and his collaborators, see, e.g., [16].
For any , we denote by the linear space of polynomials of degree no greater than and by the set of all polynomials of degree .
A sequence such that for every is called a polynomial sequence.
A polynomial sequence is called of binomial type if for any the following equalities
(17) |
hold. We get and by induction we obtain for any . Set
The space of all linear operators will be denoted by . Among these operators an important role will be played by the shift operators, named , defined by
An operator which switches with all shift operators, that is for every , is called a shift-invariant operator and the set of these operators are denoted by .
An operator is called a delta operator if and is a nonzero constant. Let denote the set of all delta operators. More generally, according to [16, Proposition 2] for every we have
A polynomial sequence is called the sequence of basic polynomials associated to the delta operator if, for any and , we get
(i) ,
(ii) ,
(iii) .
It was proved [16, Proposition 3] that every delta operator has a unique sequence of basic polynomials.
For a good understanding, we collect below some results established in [16] on this topic.
(a) If is a basic sequence for some delta operator , then it is a sequence of binomial type. Reciprocally, if is a sequence of binomial type, then it is a basic sequence for some delta operator.
(b) Let and with the basic sequence . One has
(c) An isomorphism exists from the ring of the formal power series in the variable over field, onto such that
(18) |
(d) An operator is a delta operator if and only if it corresponds under the isomorphism defined by (18), to a formal series such that and .(e) Let with its sequence of basic polynomials. Led and be the inverse formal series of , where indicates the derivative operator. Then one has
(19) |
where has the form .
At this moment we are ready to present a new class of operators. Let be a delta operator and be its sequence of basic polynomials under the additional assumption for every . We define as follows
(20) |
P. Sablonniere [18] called them Bernstein-Sheffer operators, but as D.D. Stancu and M.R. Occorsio motivated in [20] these operators can be namely Popoviciu operators. These operators check all the requirements in order to be able to create the multidimensional operators , see (9).
The operators , , are linear and reproduce the constants. Indeed, choosing in (17) , from (20) we obtain . The positivity of these operators are given by the sign of the coefficients of the series defined at (19). Tiberiu Popoviciu [14] and later P. Sablonniere [18, Theorem 1] have established the following result.
Further, from the definition of basic polynomials we get , consequently for and . It remains to check if is a contraction. Let and belong to , where , are arbitrarily fixed. Using (20) we can write
Due to positivity of operators, , see relation (21) corroborated with (19), we have . Thus, we deduce that is a contraction and
Considering that the additional condition (21) occurs, we can apply our result for multidimensional operators. Consequently, we state that (11) is valid for .
Remark. We can show that a particular case of operators defined by (20) leads us to Cheney-Sharma operators discussed in Application 2. Let be a fixed non-negative parameter. We define the following sequence of polynomials
It represents Abel sequence and verifies relation (17). Further, we consider Abel operator . For every ,
In this case forms the sequence of basic polynomials associated to delta operator . Choosing in (20) one obtains Cheney-Sharma operator and .
We end this application by indicating Crăciun’s paper [6]. Here a more complex class of linear operators is built that mixes two sequences , , the first containing basic polynomials associated to a delta operator and the second is defined by the identity , where is an invertible shift invariant operator.
References
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- [2] Agratini, O., Rus, I.A., Iterates of some bivariate approximation process via weakly Picard operators, Nonlinear Anal. Forum, 8(2003), No. 2, 159-168.
- [3] Berinde, V., Approximating fixed points of weak contractions using Picard iteration, Nonlinear Anal. Forum, 9(2004), No. 1, 43-53.
- [4] Cătinaş, T., Iterates of a modified Bernstein type operator, J. Numer. Anal. Approx. Theory, 48(2019), No. 2, 144-147.
- [5] Cheney, E.W., Sharma, A., On a generalization of Bernstein polynomials, Riv. Mat. Univ. Parma (2), 5(1964), 77-84.
- [6] Crăciun, M., Approximation operators constructed by means of Sheffer sequences, Rev. Anal. Numér. Théor. Approx., 30(2001), No. 2, 135-150.
- [7] Filip, A.-D., Petruşel, A., Existence and uniqueness of the solution for a general system of Fredholm integral equations, Math. Methods Appl. Sci., (2020), doi.org/10.1002/mma.6737.
- [8] Cvetković, M., Rakoc̆ević, V., Extensions of Perov theorem, Carpathian J. Math., 31(2015), No. 2, 181-188.
- [9] Gavrea, I., Ivan, M., On the iterates of positive linear operators preserving the affine functions, J. Math. Anal. Appl., 372(2010), 366-368.
- [10] Jensen, J.L.W.V., Sur une identité d’Abel et sur d’autres formules analogues, Acta Math., 26(1902), 307-318.
- [11] Kelisky, R.P., Rivlin, T.J., Iterates of Bernstein operators, Pacific J. Math., 21(1967), 511-520.
- [12] Novac, A., Precup, R., Perov type results in gauge spaces and their applications to integral systems on semi-axis, Math. Slovaca, 64(2014), 961-972.
- [13] Perov, A.I., On Cauchy problem for a system of ordinary differential equation, Priblizhen. Metody Reshen. Differ. Uravn., 2(1964), 115-134.
- [14] Popoviciu, T., Remarques sur le polynômes binomiaux, Bul. Soc. Sci. Cluj (Roumanie), 6(1931), 146-148 (also reproduced in Mathematica (Cluj), 6(1932), 8-10).
- [15] Precup, R., The role of matrices that are convergent to zero in the study of semilinear operator systems, Math. Comput. Modelling, 49(2009), 703-708.
- [16] Rota, G.-C., Kahaner, D., Odlyzko, A., On the Foundations of Combinatorial Theory. VIII. Finite operator calculus, J. Math. Anal. Appl., 42(1973), 685-760.
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- [18] Sablonniere, P., Positive Bernstein-Sheffer operators, J. Approx. Theory, 83(1995), 330-341.
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- [20] Stancu, D.D., Occorsio, M.R., On approximation by binomial operators of Tiberiu Popoviciu type, Rev. Anal. Numér. Théor. Approx., 27(1998), No. 1, 167-181.
- [21] Zeidler, E., Nonlinear Functional Analysis and Its Applications: Fixed-point Theorems, Transl. from the German by Peter R. Wadsack, Springer New York, 1993.
[1] Agratini, O., Rus, I. A. Iterates of a class of discrete linear operators via contraction principle. Comment. Math. Univ. Carolinae 44 (2003), 555–563.
[2] Agratini, O., Rus, I.A. Iterates of some bivariate approximation process via weakly Picard operators. Nonlinear Anal. Forum 8 (2003), no. 2, 159–168.
[3] Berinde, V., Approximating fixed points of weak contractions using Picard iteration. Nonlinear Anal. Forum 9 (2004), no. 1, 43–53.
[4] Catinas, T., Iterates of a modified Bernstein type operator. J. Numer. Anal. Approx. Theory 48 (2019), no. 2, 144–147.
[5] Cheney, E. W., Sharma, A., On a generalization of Bernstein polynomials. Riv. Mat. Univ. Parma (2) 5 (1964), 77–84.
[6] Craciun, M., Approximation operators constructed by means of Sheffer sequences. Rev. Anal. Numer. Theor. Approx. 30 (2001), no. 2, 135–150.
[7] Cvetkovic, M., Rakocevic, V., Extensions of Perov theorem. Carpathian J. Math. 31 (2015), no. 2, 181–188.
[8] Filip, A.-D., Petrusel, A,. Existence and uniqueness of the solution for a general system of Fredholm integral equations. Math. Methods Appl. Sci. (2020), doi.org/10.1002/mma.6737.
[9] Gavrea, I., Ivan, M., On the iterates of positive linear operators preserving the affine functions. J. Math. Anal. Appl. 372 (2010), 366–368.
[10] Jensen, J. L., W. V. Sur une identite d’Abel et sur d’autres formules analogues. Acta Math. 26 (1902), 307–318.
[11] Kelisky, R. P., Rivlin, T. J. Iterates of Bernstein operators. Pacific J. Math. 21 (1967), 511–520.
[12] Novac, A., Precup, R. Perov type results in gauge spaces and their applications to integral systems on semi-axis. Math. Slovaca 64 (2014), 961–972.
[13] Perov, A. I., On Cauchy problem for a system of ordinary differential equation. Priblizhen. Metody Reshen. Differ. Uravn. 2 (1964), 115–134.
[14] Popoviciu, T., Remarques sur le polynomes binomiaux. Bul. Soc. Sci. Cluj (Roumanie) 6 (1931), 146–148 (also reproduced in Mathematica (Cluj) 6 (1932), 8–10).
[15] Precup, R., The role of matrices that are convergent to zero in the study of semilinear operator systems. Math. Comput. Modelling 49 (2009), 703–708.
[16] Rota, G.-C., Kahaner, D.; Odlyzko, A. On the Foundations of Combinatorial Theory. VIII. Finite operator calculus. J. Math. Anal. Appl. 42 (1973), 685–760.
[17] Rus, I. A., Iterates of Bernstein operators, via contraction principle. J. Math. Anal. Appl. 292 (2004), 259–261.
[18] Sablonniere, P. Positive Bernstein-Sheffer operators. J. Approx. Theory 83 (1995), 330–341.
[19] Stancu, D. D., Cismasiu, C. On an approximating linear positive operators of Cheney-Sharma. Rev. Anal. Numer. Theor. Approx. 26 (1997), nos. 1–2, 221–227.
[20] Stancu, D. D., Occorsio, M. R. On approximation by binomial operators of Tiberiu Popoviciu type. Rev. Anal. Numer. Theor. Approx. 27 (1998), no. 1, 167–181.
[21] Zeidler, E., Nonlinear Functional Analysis and Its Applications: Fixed-point Theorems. Transl. from the German by Peter R. Wadsack, Springer New York, 1993.