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Linear Estimation and Detection in Krylov Subspaces (Foundations in Signal Processing, Communications and Networking (1)) 🔍
Guido K. E. Dietl Springer Spektrum. in Springer-Verlag GmbH, Foundations in signal processing, communications and networking -- v. 1, Berlin, New York, Germany, 2007
英语 [en] · PDF · 3.2MB · 2007 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save
描述
One major area in the theory of statistical signal processing is reduced-rank - timation where optimal linear estimators are approximated in low-dimensional subspaces, e.g., in order to reduce the noise in overmodeled problems, - hance the performance in case of estimated statistics, and/or save compu- tional complexity in the design of the estimator which requires the solution of linear equation systems. This book provides a comprehensive overview over reduced-rank ?lters where the main emphasis is put on matrix-valued ?lters whose design requires the solution of linear systems with multiple right-hand sides. In particular, the multistage matrix Wiener ?lter, i.e., a reduced-rank Wiener ?lter based on the multistage decomposition, is derived in its most general form. In numerical mathematics, iterative block Krylov methods are very po- lar techniques for solving systems of linear equations with multiple right-hand sides, especially if the systems are large and sparse. Besides presenting a - tailed overview of the most important block Krylov methods in Chapter 3, which may also serve as an introduction to the topic, their connection to the multistage matrix Wiener ?lter is revealed in this book. Especially, the reader will learn the restrictions of the multistage matrix Wiener ?lter which are necessary in order to end up in a block Krylov method. This relationship is of great theoretical importance because it connects two di?erent ?elds of mathematics, viz., statistical signal processing and numerical linear algebra.
Erscheinungsdatum: 20.07.2007
备用文件名
lgli/Linear Estimation and Detection in Krylov Subspaces (Foundations in Signal Processing, Communications and Networking) (Springer ,2007)ISBN978-3-540-68478-7.pdf
备用文件名
lgrsnf/Linear Estimation and Detection in Krylov Subspaces (Foundations in Signal Processing, Communications and Networking) (Springer ,2007)ISBN978-3-540-68478-7.pdf
备用文件名
zlib/Mathematics/Linear Estimation and Detection in Krylov Subspaces_635859.pdf
备选标题
Well-posed linear systems
备选作者
Olof J Staffans; NetLibrary, Inc
备选作者
Dietl, Guido K. E.
备用出版商
Cambridge University Press (Virtual Publishing)
备用出版商
Steinkopff. in Springer-Verlag GmbH
备用出版商
Greenwich Medical Media Ltd
备用出版商
Springer Berlin
备用版本
Encyclopedia of mathematics and its applications -- v. 103, Encyclopedia of mathematics and its applications -- v. 103., Cambridge, UK, New York, England, 2005
备用版本
Foundations in Signal Processing, Communications and Networking, 1, Berlin, Heidelberg, 2007
备用版本
United Kingdom and Ireland, United Kingdom
备用版本
Springer Nature, Berlin, 2007
备用版本
Germany, Germany
元数据中的注释
lg208113
元数据中的注释
{"isbns":["0511082088","9780511082085"],"last_page":238,"publisher":"Springer","series":"Foundations in Signal Processing, Communications and Networking"}
元数据中的注释
Includes bibliographical references and index.
元数据中的注释
Includes bibliographical references (p. 750-766) and index.
Description based on print version record.
备用描述
<p><P>This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communications systems.<p>The investigations include exact computational complexity considerations and performance analysis based on extrinsic information transfer charts as well as Monte-Carlo simulations.</p>
备用描述
"This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented." "In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems."--Jacket
备用描述
Cover; Series-title; Title; Copyright; Contents; Figures; Preface; Notation; 1 Introduction and overview; 2 Basic properties of well-posed linear systems; 3 Strongly continuous semigroups; 4 The generators of well-posed linear system; 5 Compatible and regular systems; 6 Anti-causal, dual, and inverted systems; 7 Feedback; 8 Stabilization and detection; 9 Realizations; 10 Admissibility; 11 Passive and conservative scattering systems; 12 Discrete time systems; Appendix; Bibliography; Index.
备用描述
Much of the material that the author presents is original and many results have never appeared in book form before. A comprehensive bibliography completes this work which will be indispensable to all working in systems theory, operator theory, delay equations and partial differential equations.
开源日期
2010-02-18
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