- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Abstract and Applied Analysis
Volume 2014 (2014), Article ID 437506, 19 pages
Error Estimate of Eigenvalues of Perturbed Higher-Order Discrete Vector Boundary Value Problems
1School of Mathematics and Statistics, Anyang Normal University, Anyang, Henan 455000, China
2School of Mathematics, Shandong University, Jinan, Shandong 250100, China
3School of Statistics and Mathematics, Shandong Provincial Key Laboratory of Digital Media Technology, Shandong University of Finance and Economics, Jinan, Shandong 250014, China
Received 23 November 2013; Accepted 30 December 2013; Published 17 February 2014
Academic Editor: Allan Peterson
Copyright © 2014 Haiyan Lv et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper is concerned with the eigenvalues of perturbed higher-order discrete vector boundary value problems. A suitable admissible function space is first introduced, a new variational formula of eigenvalues is then established under certain nonsingularity conditions, and error estimates of eigenvalues of problems with small perturbation are finally given by using the variational formula. As a direct consequence, continuous dependence of eigenvalues on boundary value problems is obtained under the nonsingularity conditions. In addition, two special perturbed cases are discussed.
Consider the following -order vector difference equation: with the boundary condition whereis the forward difference operator; that is, ; is a -dimensional column vector-valued function on interval of integer, and ; () and () are Hermitian matrices, (); and are matrices satisfying the following self-adjoint condition [1, Lemma 2.1]: , are -dimensional vectors; denotes the transpose of ; denotes the complex conjugate transpose of ; and is the spectral parameter.
Higher-order discrete linear problems also have been investigated by some scholars besides second-order discrete Sturm-Liouville problems and discrete linear Hamiltonian systems (cf. [2–14] and their references). Zhou  and Grzegorczyk and Werbowski  studied a higher-order linear difference equation in which the leading coefficient is equal to 1 and established some criteria for the oscillation of solutions. Shi and Chen  investigated higher-order discrete linear boundary value problems (1)-(2) and obtained some spectral results, including Rayleigh’s principle, the minimax theorem, the dual orthogonality, and the number of eigenvalues. These results establish the theoretical foundation for our further research. Ren and Shi  discussed the defect index of singular symmetric linear difference equations of order with real coefficients and one singular endpoint and showed that the defect index satisfies the inequalities and that all values of in this range are realized. However, because of the characteristics of higher-order difference equations, compared with the research of second-order difference equations and discrete Hamiltonian systems, it is more difficult to study higher-order difference equations. Thus, there are few references in higher-order difference equations. For more information about higher-order discrete linear problems, the reader is referred to [6, 12, 14].
Recently, we have studied second-order discrete Sturm-Liouville problems and obtained error estimates of eigenvalues of perturbed problem under some hypotheses in . Motivated by the ideas and methods used in , we extend the results to -order discrete vector boundary value problems (1)-(2) by means of the results obtained in . Although the method is similar, the problems we investigate in this paper are more complex, since they are not only of higher order but also of higher dimension.
However, hypothesis (3) does not require the leading coefficient to be always nonsingular in . So, the coefficient and the weight functions of the corresponding discrete linear Hamiltonian system do not satisfy assumption (2.1) and the positive definiteness of the weight function in . Hence the Hamiltonian system considered in  does not include the equation we discuss in this paper.
In the present paper, we study error estimate of eigenvalues of (1)-(2) under small perturbation. By employing a variational property—the minimax theorem established in —an error estimate of eigenvalues of all perturbed problems sufficiently close to problem (1)-(2) is given under certain nonsingularity conditions. The continuous dependence of eigenvalues on problems is consequently obtained from the error estimate under the nonsingularity conditions. The continuous dependence of eigenvalues on problems may not hold in general. It is under certain nonsingularity conditions that we get the related result. In addition, the minimax theorem [1, Theorem 3.5] was established in an admissible function space, which is dependent on boundary condition (2). Hence, it is difficult to apply to the case that some perturbation occurs in boundary condition (2). So we will first establish a minimax theorem in an admissible function space with a new weight function that includes the data of (1) and boundary condition (2) by [1, Theorem 3.5]. Then, employing the new minimax theorem, we study the error estimate of eigenvalues of perturbed problem. Another difficulty results from the complicated calculations since the problem is not only of higher order but also of higher dimension and needs to estimate the norms of inverses of some perturbed matrices.
The setup of this paper is as follows. In the next section, we recall some useful existing results, introduce a new suitable admissible function space, and establish a new minimax theorem in it. In Section 3, we give the main results that provide error estimates of eigenvalues of perturbed problems of (1)-(2) under certain nonsingularity conditions. Finally, We discuss two special perturbed problems in Section 4.
In this section, we first introduce some notations and results for convenience in the following discussion, then give a suitable admissible function space, and establish a new variational property of eigenvalues for (1)-(2) in this space.
Consider the following linear space:
Obviously, . Let denote the following difference operator:
For convenience, for , we write if satisfies boundary condition (2). Denote
Express and in terms of : where , , , and and are matrices; and are matrices about , which are the shifts of variable of in and to the right with units, respectively. More precisely, for , ,
Next, we always assume that
The Rayleigh quotient for the difference operator on with is defined by where and .
From above we know that , and then can be uniquely determined by . Hence, we introduce the following new admissible function space:
Thus, we can define an inner product on by where , . Denote its induced norm by
In order to establish a connection between and , we define a linear map by with determined by (28) for . Evidently, is an invertible linear map. Moreover, for any , , set and . Then, from (23), (27), and (30), we have that is, is a product-preserving map.
For any , , and , are matrices, are matrices, and
Further, it follows from (27) that where
At the end of this section, we quote two lemmas about matrices and their perturbation. For convenience, we introduce the following notation for an invertible matrix : where the norm of matrix is defined by
With the aid of [9, Corollary 7.8.2] we have immediately the following results.
Lemma 5. For any matrix , .
Lemma 6 ([17, Lemma 2.5]). Let be invertible. If a matrix satisfies then is invertible, and
3. Main Results
For convenience, introduce the following notations and several constant matrices:
For any , , where denotes the minimum value of all eigenvalues of and is the same as in (30). It is evident that and .
Based on the above discussion, we know
In the following, we will prove that if the perturbation is sufficiently small in norm, then where has the same form of with in (18) replaced by . The matrices , , , (), () are the perturbations of the matrices , , , (), (), respectively.
Proof. (i) We only prove that is invertible. The invertibility of can be similarly proved. Since
Thus, is invertible by Lemma 6, and
In addition, since then is nonsingular on , which, together with the invertibility of , yields that (52) holds. So (i) is proved.
(ii) Let be a submatrix of and let its position be the same as that of in . Since that is,
is invertible by Lemma 6 and, consequently, .
Then we have
Hence, is invertible and by Lemma 6. Further, which yields that (59) holds. The proof is complete.
Under the assumptions of Proposition 7, and are invertible. So, we can define the following inner product on corresponding to problem -: for any , , where
The corresponding induced norm is denoted by
Similarly, is also an -dimensional Hilbert space.
According to the above discussion, if (51), (55), and (56) hold, then we can get the following variational formula of eigenvalues for - on in a similar way to Theorem 4: for each , , with , where denotes .
In order to obtain an error estimate of eigenvalues for the perturbed problem by applying the above variational formula of eigenvalues, we will discuss the relationship between and and then give another form of variational formula of eigenvalues for - on . Now we introduce the following linear transformation: where, for any
Obviously, is invertible, and
So, for any , we get
Before giving the main results, we prepare some estimates.
Proof. denotes the adjoint matrix of . Then, by Lemma 5, we get
Similarly, one gets
Hence, we have from (57) and (89) that
Similarly, we obtain
It follows from (41) and (77) that
From (91) one can get
Therefore, we have
It is easy to get from (41) that
Inequality (86) can be obtained by a similar argument. The proof is complete.
Now, we study for any .
Next, we study the difference between and for any .
Proof. It follows from (80) that, for any given ,
which, together with (33), yields that
Since it follows from Lemma 6 that
Similarly, we have
In addition, from (59), (71), and (113) we get
Now, we are in a position to estimate . Let
Then, from (89) we obtain
With a similar argument to that for (93), we get
From (67) one has which, together with (69), implies that
Hence, it follows from (30), (71), and (121) that whereis the same as in (108). It can be easily concluded from (69) that
Therefore, from (113), (116), (122), and (123) we have
Consequently, (106) holds and the proof is complete.
The following result is about the estimate of difference betweenand.