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Main Authors: Bakhit, Mohammed, Khattak, Faizan A., Proudler, Ian K., Weiss, Stephan
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.20268
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author Bakhit, Mohammed
Khattak, Faizan A.
Proudler, Ian K.
Weiss, Stephan
author_facet Bakhit, Mohammed
Khattak, Faizan A.
Proudler, Ian K.
Weiss, Stephan
contents A matrix of analytic functions A(z), such as the matrix of transfer functions in a multiple-input multiple-output (MIMO) system, generally admits an analytic singular value decomposition (SVD), where the singular values themselves are functions. When evaluated on the unit circle, for the sake of analyticity, these singular values must be permitted of become negative. In this paper, we address how the estimation of such a matrix, causing a stochastic perturbation of A}(z), results in fundamental changes to the analytic singular values: for the perturbed system, we show that their analytic singular values lose any algebraic multiplicities and are strictly non-negative with probability one. We present examples and highlight the impact that this has on algorithmic solutions to extracting an analytic or approximate analytic SVD.
format Preprint
id arxiv_https___arxiv_org_abs_2409_20268
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Impact of Estimation Errors of a Matrix of Transfer Functions onto Its Analytic Singular Values and Their Potential Algorithmic Extraction
Bakhit, Mohammed
Khattak, Faizan A.
Proudler, Ian K.
Weiss, Stephan
Signal Processing
A matrix of analytic functions A(z), such as the matrix of transfer functions in a multiple-input multiple-output (MIMO) system, generally admits an analytic singular value decomposition (SVD), where the singular values themselves are functions. When evaluated on the unit circle, for the sake of analyticity, these singular values must be permitted of become negative. In this paper, we address how the estimation of such a matrix, causing a stochastic perturbation of A}(z), results in fundamental changes to the analytic singular values: for the perturbed system, we show that their analytic singular values lose any algebraic multiplicities and are strictly non-negative with probability one. We present examples and highlight the impact that this has on algorithmic solutions to extracting an analytic or approximate analytic SVD.
title Impact of Estimation Errors of a Matrix of Transfer Functions onto Its Analytic Singular Values and Their Potential Algorithmic Extraction
topic Signal Processing
url https://arxiv.org/abs/2409.20268