Linear Algebra : A Problem-Centered Approach
by
Robert Freud
Book Details
Format
Paperback / Softback
Book Series
Pure and Applied Undergraduate Texts
ISBN-10
147047736X
ISBN-13
9781470477363
Publisher
American Mathematical Society
Imprint
American Mathematical Society
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 1st, 2024
Print length
305 Pages
Product Classification:
AlgebraAlgebraic geometry
Ksh 13,700.00
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This textbook invites readers to dive into the mathematical ideas of linear algebra. Offering a gradual yet rigorous introduction, the author illuminates the structure, order, symmetry, and beauty of the topic. Opportunities to explore, master, and extend the theory abound, with generous exercise sets embodying the Hungarian tradition of active problem-solving. Determinants, matrices, and systems of linear equations begin the book. This unique ordering offers insights from determinants early on, while also admitting re-ordering if desired. Chapters on vector spaces, linear maps, and eigenvalues and eigenvectors follow. Bilinear functions and Euclidean spaces build on the foundations laid in the first half of the book to round out the core material. Applications in combinatorics include Hilbert's third problem, Oddtown and Eventown problems, and Sidon sets, a favorite of Paul Erdos. Coding theory applications include error-correction, linear, Hamming, and BCH codes. An appendix covers the algebraic basics used in the text. Ideal for students majoring in mathematics and computer science, this textbook promotes a deep and versatile understanding of linear algebra. Familiarity with mathematical proof is assumed, though no prior knowledge of linear algebra is needed. Supplementary electronic materials support teaching and learning, with selected answers, hints, and solutions, and an additional problem bank for instructors.
Explore a rigorous journey through linear algebra where structure, symmetry, and theory reveal themselves gradually. Engaging exercises rooted in active problem-solving guide you from determinants and matrices to vector spaces and eigenvalues while linking concepts to combinatorics and coding theory.
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