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9780898716719 Academic Inspection Copy

Generalized Inverses of Linear Transformations

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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; 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.
Stephen L. Campbell is Professor of Mathematics and Director of Graduate Programs at North Carolina State University. His research interests include linear algebra, control theory, differential equations (especially differential algebraic equations), numerical methods, and applications. He is the author or co-author of eight books. Carl D. Meyer is Professor of Mathematics at North Carolina State University. His research interests include numerical and applied linear algebra; Markov chains and applied probability; and information retrieval, data mining, and web search. He is the author or co-author of six books.
Preface to the Classics Edition Preface Chapter 0: Introduction and other preliminaries Chapter 1: The Moore-Penrose or generalized inverse Chapter 2: Least squares solutions Chapter 3: Sums, partitioned matrices and the constrained generalized inverse Chapter 4: Partial isometries and EP matrices Chapter 5: The generalized inverse in electrical engineering Chapter 6: (i, j, k)-Generalized inverses and linear estimation Chapter 7: The Drazin inverse Chapter 8: Applications of the Drazin inverse to the theory of finite Markov chains Chapter 9: Applications of the Drazin inverse Chapter 10: Continuity of the generalized inverse Chapter 11: Linear programming Chapter 12: Computational concerns Bibliography Index
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