1991SIAM Journal on Matrix Analysis and ApplicationsRequires access

On the Inverse M-Matrix Problem for Real Symmetric Positive-Definite Toeplitz Matrices

I. Koltracht, Michael Neumann

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Abstract

Necessary and sufficient conditions are obtained for a real symmetric positive-definite Toeplitz matrix R to be an inverse of an M-matrix in terms of its Schur coefficients. Related problems are also considered, such as when such a matrix R can be extended to a higher-dimensional real symmetric positive-definite Toeplitz matrix whose inverse is an M-matrix or, under less restrictive conditions on R, when only its Cholesky factors are inverses of M-matrices. The proofs are constructive and allow the generation of such R’s with the various aforementioned properties.

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What this paper is about

Necessary and sufficient conditions are obtained for a real symmetric positive-definite Toeplitz matrix R to be an inverse of an M-matrix in terms of its Schur coefficients. Related problems are also considered, such as when such a matrix R can be extended to a higher-dimensional real symmetric positive-definite Toeplitz matrix whose inverse is an M-matrix or, under less restrictive conditions on R, when only its Cholesky factors are inverses of M-matrices. The proofs are constructive and allow the generation of such R’s with the various aforementioned properties.

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Available abstract

Necessary and sufficient conditions are obtained for a real symmetric positive-definite Toeplitz matrix R to be an inverse of an M-matrix in terms of its Schur coefficients. Related problems are also considered, such as when such a matrix R can be extended to a higher-dimensional real symmetric positive-definite Toeplitz matrix whose inverse is an M-matrix or, under less restrictive conditions on R, when only its Cholesky factors are inverses of M-matrices. The proofs are constructive and allow the generation of such R’s with the various aforementioned properties.

Key concepts: Toeplitz matrix, Mathematics, Positive-definite matrix, Cholesky decomposition, Levinson recursion, Symmetric matrix, Inverse, Matrix (chemical analysis)

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