Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Generalized Inverses of Linear Transformations (Classics in Applied Mathematics)

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Stephen L. Campbell 作者
Society for Industrial and Applied Mathematics
譯者
2008-12-16 出版日期
184 頁數
USD 68.00 價格
Paperback
叢書系列
9780898716719 圖書編碼

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Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 著者簡介


Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 著者簡介


Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Generalized Inverses of Linear Transformations (Classics in Applied Mathematics) 在線電子書 圖書描述

Generalized (or pseudo-) inverse concepts routinely appear throughout applied mathematics and engineering, in both research literature and textbooks. Although the basic properties are readily available, some of the more subtle aspects and difficult details of the subject are not well documented or understood. This book is an excellent reference for researchers and students who need or want more than just the most basic elements. First published in 1979, the book remains up-to-date and readable, and it includes chapters on Markov chains and the Drazin inverse methods that have become significant to many problems in applied mathematics. Generalized Inverses of Linear Transformations provides comprehensive coverage of the mathematical theory of generalized inverses coupled with a wide range of important and practical applications that includes topics in electrical and computer engineering, control and optimization, computing and numerical analysis, statistical estimation, and stochastic processes.

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