Low-Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering)
暫譯: 低秩近似：演算法、實作與應用（通訊與控制工程）
Ivan Markovsky
- 出版商: Springer
- 出版日期: 2018-08-17
- 售價: $6,250
- 貴賓價: 9.5 折 $5,938
- 語言: 英文
- 頁數: 272
- 裝訂: Hardcover
- ISBN: 3319896199
- ISBN-13: 9783319896199
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相關分類:
Algorithms-data-structures
海外代購書籍(需單獨結帳)
商品描述
This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required.
The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of:
• variable projection for structured low-rank approximation;
• missing data estimation;
• data-driven filtering and control;
• stochastic model representation and identification;
• identification of polynomial time-invariant systems; and
• blind identification with deterministic input model.
The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis.
“Each chapter is completed with a new section of exercises to which complete solutions are provided.”
Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
商品描述(中文翻譯)
這本書全面闡述了結構性低秩近似的理論、算法和應用。書中介紹了局部優化方法以及針對Toeplitz、Hankel和Sylvester結構問題的有效次優凸鬆弛。文本的主要部分專注於理論的應用，涵蓋了從系統與控制理論到心理測量學的一系列應用，並不需要對應用領域有特別的知識。
《低秩近似》（第二版）是經過徹底編輯和廣泛重寫的修訂版。它包含了新章節和部分，介紹以下主題：
• 結構性低秩近似的變量投影；
• 缺失數據估計；
• 基於數據的過濾和控制；
• 隨機模型表示和識別；
• 多項式時間不變系統的識別；以及
• 具有確定性輸入模型的盲識別。
本書還附有所介紹方法的軟體實現，使理論能夠直接應用於實踐。特別是，書中的所有數值範例都包含在演示檔案中，讀者可以重現這些範例。這提供了與詳細理論和方法的實踐經驗。此外，練習題和MATLAB^® /Octave範例將幫助讀者逐章快速吸收理論。
“每章都附有一個新的練習題部分，並提供完整的解答。”
《低秩近似》（第二版）是對低秩近似理論及其應用領域的廣泛調查，將直接吸引系統識別、控制與系統理論、數值線性代數和優化領域的研究人員。補充問題和解答使其適合用於教授這些科目的研究生課程。
