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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'Matrix analysis is the engine room of scientific computing since, inevitably, most computational problems are reduced to linear algebra. Xian-Da Zhang's monograph presents a thoroughly modern introduction to this important subject in a form suitable for its many users. Without taking liberties with mathematical content, the text privileges an algorithmic approach and ventures into new and important areas, e.g. tensor analysis. This is a valuable addition to any applied mathematician's bookshelf.' Arieh Iserles, University of Cambridge