Linear Algebra

Algorithms, Applications, and Techniques

Nonfiction, Science & Nature, Mathematics, Number Theory, Algebra
Cover of the book Linear Algebra by Richard Bronson, Gabriel B. Costa, John T. Saccoman, Elsevier Science
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Author: Richard Bronson, Gabriel B. Costa, John T. Saccoman ISBN: 9780123978110
Publisher: Elsevier Science Publication: October 8, 2013
Imprint: Academic Press Language: English
Author: Richard Bronson, Gabriel B. Costa, John T. Saccoman
ISBN: 9780123978110
Publisher: Elsevier Science
Publication: October 8, 2013
Imprint: Academic Press
Language: English

In this appealing and well-written text, Richard Bronson starts with the concrete and computational, and leads the reader to a choice of major applications. The first three chapters address the basics: matrices, vector spaces, and linear transformations. The next three cover eigenvalues, Euclidean inner products, and Jordan canonical forms, offering possibilities that can be tailored to the instructor's taste and to the length of the course. Bronson's approach to computation is modern and algorithmic, and his theory is clean and straightforward. Throughout, the views of the theory presented are broad and balanced and key material is highlighted in the text and summarized at the end of each chapter. The book also includes ample exercises with answers and hints.

Prerequisite: One year of calculus is recommended.

  • Introduces deductive reasoning and helps the reader develop a facility with mathematical proofs
  • Provides a balanced approach to computation and theory by offering computational algorithms for finding eigenvalues and eigenvectors
  • Offers excellent exercise sets, ranging from drill to theoretical/challeging along with useful and interesting applications not found in other introductory linear algebra texts
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In this appealing and well-written text, Richard Bronson starts with the concrete and computational, and leads the reader to a choice of major applications. The first three chapters address the basics: matrices, vector spaces, and linear transformations. The next three cover eigenvalues, Euclidean inner products, and Jordan canonical forms, offering possibilities that can be tailored to the instructor's taste and to the length of the course. Bronson's approach to computation is modern and algorithmic, and his theory is clean and straightforward. Throughout, the views of the theory presented are broad and balanced and key material is highlighted in the text and summarized at the end of each chapter. The book also includes ample exercises with answers and hints.

Prerequisite: One year of calculus is recommended.

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