Nonnegative Matrices and Applicable Topics in Linear Algebra

Alexander Graham

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English

Dover
01 February 2020

Mathematics & Sciences; Mathematics

Nonnegative matrices is an increasingly important subject in economics, control theory, numerical analysis, Markov chains, and other areas. This concise treatment is directed toward undergraduates who lack specialized knowledge at the postgraduate level of mathematics and related fields, such as mathematical economics and operations research.

An Introductory Survey encompasses some aspects of matrix theory and its applications and other relevant topics in linear algebra, including certain facets of graph theory. Subsequent chapters cover various points of the theory of normal matrices, comprising unitary and Hermitian matrices, and the properties of positive definite matrices. An exploration of the main topic, nonnegative matrices, is followed by a discussion of M-matrices. The final chapter examines stochastic, genetic, and economic models. The important concepts are illustrated by simple worked examples. Problems appear at the conclusion of most chapters, with solutions at the end of the book.

AUTHOR: Alexander Graham, now retired, was Senior Lecturer on the Faculty of Mathematics at The Open University, Milton Keynes, U.K. Dover also publishes his Matrix Theory and Applications for Scientists and Engineers, and Kronecker Products and Matrix Calculus with Applications.

By: Alexander Graham
Imprint: Dover
Country of Publication: United States
Dimensions: Height: 228mm, Width: 153mm, Spine: 14mm
Weight: 385g
ISBN: 9780486838076
ISBN 10: 0486838072
Pages: 272
Publication Date: 01 February 2020
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Paperback
Publisher's Status: Unspecified

Alexander Graham, now retired, was Senior Lecturer on the Faculty of Mathematics at The Open University, Milton Keynes, U.K. Dover also publishes his Matrix Theory and Applications for Scientists and Engineers, and Kronecker Products and Matrix Calculus with Applications.