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Titlebook: Algorithms for Quadratic Matrix and Vector Equations; Federico Poloni Book 2011 The Editor(s) (if applicable) and The Author(s), under exc

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樓主
發(fā)表于 2025-3-21 18:58:03 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Algorithms for Quadratic Matrix and Vector Equations
影響因子2023Federico Poloni
視頻videohttp://file.papertrans.cn/154/153232/153232.mp4
發(fā)行地址Contains a new unifying approach to quadratic vector and matrix equations in applied probability.Gives new insight on the structured doubling algorithm which can be exploited to develop suitable modif
學(xué)科分類Publications of the Scuola Normale Superiore
圖書封面Titlebook: Algorithms for Quadratic Matrix and Vector Equations;  Federico Poloni Book 2011 The Editor(s) (if applicable) and The Author(s), under exc
影響因子This book is devoted to studying algorithms for the solution of a class of quadratic matrix and vector equations. These equations appear, in different forms, in several practical applications, especially in applied probability and control theory. The equations are first presented using a novel unifying approach; then, specific numerical methods are presented for the cases most relevant for applications, and new algorithms and theoretical results developed by the author are presented. The book focuses on “matrix multiplication-rich” iterations such as cyclic reduction and the structured doubling algorithm (SDA) and contains a variety of new research results which, as of today, are only available in articles or preprints.
Pindex Book 2011
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沙發(fā)
發(fā)表于 2025-3-21 20:32:45 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:19:40 | 只看該作者
Jürgen Isberg,Hans-Horst RosackerThe problem of reducing an algebraic Riccati equation (5) to a unilateral quadratic matrix equation (2) has been considered in [32, 73, 95, 109, 138].
地板
發(fā)表于 2025-3-22 06:00:12 | 只看該作者
5#
發(fā)表于 2025-3-22 11:02:45 | 只看該作者
6#
發(fā)表于 2025-3-22 12:59:52 | 只看該作者
Storage-optimal algorithms for Cauchy-like matricesSeveral classes of algorithms for the numerical solution of Toeplitz-like and Cauchy-like linear systems exist in the literature. We refer the reader to [153] for an extended introduction on this topic, with descriptions of each method and plenty of citations to the relevant papers, and only summarize them in Table 7.1.
7#
發(fā)表于 2025-3-22 20:31:36 | 只看該作者
https://doi.org/10.33283/978-3-86298-846-4se of . The notation I., with . often omitted when it is clear from the context, denotes the identity matrix; the zero matrix of any dimension is denoted simply by 0. With . we denote the vector of suitable dimension all of whose entries are 1. The expression ρ (.) stands for the spectral radius of
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發(fā)表于 2025-3-23 05:49:54 | 只看該作者
Jürgen Isberg,Hans-Horst Rosackererical algorithms, taken mainly from [31]. Moreover, we describe several attempts to generalize the logarithmic reduction algorithm to a generic quadratic vector equation in the framework of Chapter 2, that lead to an unexpected connection with Newton’s algorithm. While the original results containe
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