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Matrix Analysis and Applications / by Xian-Da Zhang. [Electronic Resource]

By: Material type: Computer fileComputer filePublication details: Cambridge : Cambridge University Press, 2017Description: xxxvi, 723pISBN:
  • 9781108277587
Subject(s): DDC classification:
  • 512.943 4 Z28M
Online resources: Summary: This balanced and comprehensive study presents the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis in a completely new light. Alongside the core subjects in matrix analysis, such as singular value analysis, the solution of matrix equations and eigenanalysis, the author introduces new applications and perspectives that are unique to this book. The very topical subjects of gradient analysis and optimization play a central role here. Also included are subspace analysis, projection analysis and tensor analysis, subjects which are often neglected in other books. Having provided a solid foundation to the subject, the author goes on to place particular emphasis on the many applications matrix analysis has in science and engineering, making this book suitable for scientists, engineers and graduate students alike.
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Holdings
Item type Home library Collection Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Textbook 512.943 4 Z28M (Browse shelf(Opens below)) Available (e-Book For Access) Platform : Cambridge Core EB0423
Total holds: 0
Browsing S. R. Ranganathan Learning Hub shelves, Shelving location: Online, Collection: Textbook Close shelf browser (Hides shelf browser)
512.5 Se664I Introduction to Linear Algebra 512.86 Sc86G Group Theory 512.9 J151B Basic Algebra I 512.943 4 Z28M Matrix Analysis and Applications 512.9434 H78M Matrix Analysis 513.83 W661G General Topology 514 P435F Foundations of General Topology

This balanced and comprehensive study presents the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis in a completely new light. Alongside the core subjects in matrix analysis, such as singular value analysis, the solution of matrix equations and eigenanalysis, the author introduces new applications and perspectives that are unique to this book. The very topical subjects of gradient analysis and optimization play a central role here. Also included are subspace analysis, projection analysis and tensor analysis, subjects which are often neglected in other books. Having provided a solid foundation to the subject, the author goes on to place particular emphasis on the many applications matrix analysis has in science and engineering, making this book suitable for scientists, engineers and graduate students alike.

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