On multivariable matrix spectral factorization method

被引：1

作者：

Ephremidze, Lasha ^{[1
,2
]}

Spitkovsky, Ilya M. ^{[1
]}

机构：

[1] New York Univ Abu Dhabi NYUAD, Div Sci & Math, Abu Dhabi 129188, U Arab Emirates

[2] I Javakhishvili Tbilisi State Univ, Razmadze Math Inst, 6 Tamarashvili Str, GE-0177 Tbilisi, Georgia

来源：

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS | 2022年 / 514卷 / 01期

基金：

美国国家科学基金会;

关键词：

Matrix spectral factorization; Multivariable systems; Unitary matrix functions; PREDICTION THEORY; FOURIER SERIES; EXTENSIONS;

D O I：

10.1016/j.jmaa.2022.126300

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Spectral factorization is a prominent tool with several important applications in various areas of applied science. Wiener and Masani proved the existence of matrix spectral factorization. Their theorem has been extended to the multivariable case by Helson and Lowdenslager. Solving the problem numerically is challenging in both situations, and also important due to its practical applications. Therefore, several authors have developed algorithms for factorization. The Janashia-Lagvilava algorithm is a relatively new method for matrix spectral factorization which has proved to be useful in several applications. In this paper, we extend this method to the multivariable case. Consequently, a new numerical algorithm for multivariable matrix spectral factorization is constructed. (C) 2022 Elsevier Inc. All rights reserved.

引用

页数：25

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