Название: Introduction to Linear Algebra, 5th Edition
Автор: Gilbert Strang
Издательство: Wellesley - Cambridge Press
Жанр: Алгебра, обучение
Год издания: 2016
Страниц: 584
Язык: Английский
Формат: PDF
Качество: Хорошее
Размер: 62 Мб

Классический учебник линейной алгебры, по которому учатся в Массачусетском Технологическом Институте.
Gilbert Strang's textbooks have changed the entire approach to learning linear algebra – away from abstract vector spaces to specific examples of the four fundamental subspaces: the column space and nullspace of A and A'.
This new fifth edition has become more than a textbook for the basic linear algebra course. That is its first purpose and always will be. The new chapters about applications of the SVD, probability and statistics, and Principal Component Analysis in finance and genetics, make it also a textbook for a second course, plus a resource at work. Linear algebra has become central in modern applied mathematics. This book supports the value of understanding linear algebra.

Introduction to Linear Algebra, Fifth Edition includes challenge problems to complement the review problems that have been highly praised in previous editions. The basic course is followed by eight applications: differential equations in engineering, graphs and networks, statistics, Fourier methods and the FFT, linear programming, computer graphics, cryptography, Principal Component Analysis, and singular values.

Audience: Thousands of teachers in colleges and universities and now high schools are using this book, which truly explains this crucial subject. This text is for readers everywhere, with support from the websites and video lectures. Every chapter begins with a summary for efficient review.

Contents:
Chap. 1: Introduction to Vectors
Chap. 2: Solving Linear Equations
Chap. 3: Vector Spaces and Subspaces
Chap. 4: Orthogonality
Chap. 5: Determinants
Chap. 6: Eigenvalues and Eigenvectors
Chap. 7: Singular Value Decomposition
Chap. 8: Linear Transformations
Chap. 9: Complex Vectors and Matrices
Chap. 10: Applications
Chap. 11: Numerical Linear Algebra
Chap. 12: Linear Algebra in Probability and Statistics
Matrix Factorizations
Index
Six Great Theorems