Linear Algebra: Algorithms, Applications, and Techniques
Autor Richard Bronson, Gabriel B. Costa, John T. Saccoman, Daniel Grossen Limba Engleză Paperback – 20 iun 2023
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Specificații
ISBN-10: 0128234709
Pagini: 528
Dimensiuni: 191 x 235 x 30 mm
Greutate: 1.09 kg
Ediția:4
Editura: ELSEVIER SCIENCE
Cuprins
1. Matrices 2. Vector Spaces 3. Linear Transformations 4. Eigenvalues, Eigenvectors, and Differential Equations 5. Euclidean Inner Product
Appendix A. Determinants B. Jordan Canonical Forms C. Markov Chains D. The Simplex Method, an Example E. A Word on Numerical Techniques and Technology Answers And Hints To Selected Problems
Notă biografică
Richard Bronson is a Professor of Mathematics and Computer Science at Fairleigh Dickinson University and is Senior Executive Assistant to the President. Ph.D., in Mathematics from Stevens Institute of Technology. He has written several books and numerous articles on Mathematics. He has served as Interim Provost of the Metropolitan Campus, and has been Acting Dean of the College of Science and Engineering at the university in New Jersey
Descriere
Linear Algebra: Algorithms, Applications, and Techniques, Fourth Edition offers a modern and algorithmic approach to computation while providing clear and straightforward theoretical background information. The book guides readers through the major applications, with chapters on properties of real numbers, proof techniques, matrices, vector spaces, linear transformations, eigen values, and Euclidean inner products. Appendices on Jordan canonical forms and Markov chains are included for further study. This useful textbook presents broad and balanced views of theory, with key material highlighted and summarized in each chapter. To further support student practice, the book also includes ample exercises with answers and hints.
- 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/challenging, along with useful and interesting applications not found in other introductory linear algebra texts