000			03472cam a2200385 a 4500
003			OSt
005			20260817090426.0
008			050304s2006 caua 001 0 eng
020			_a0030105676
020			_a9780030105678
040			_cAKCL
082			_a512.5 _bSTR-L4
100	1		_aStrang, Gilbert.
245	1	0	_aLinear Algebra and Its Applications / _cGilbert Strang.
250			_a4th ed.
260			_aDelhi: _bCengage Learning India Pvt. Ltd., _c2025.
300			_aviii, 487 p. :
300			_c25 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
500			_aIncludes index.
505			_a1. MATRICES AND GAUSSIAN ELIMINATION. Introduction. The Geometry of Linear Equations. An Example of Gaussian Elimination. Matrix Notation and Matrix Multiplication. Triangular Factors and Row Exchanges. Inverses and Transposes. Special Matrices and Applications. Review Exercises. 2. VECTOR SPACES. Vector Spaces and Subspaces. The Solution of m Equations in n Unknowns. Linear Independence, Basis, and Dimension. The Four Fundamental Subspaces. Networks and Incidence Matrices. Linear Transformations. Review Exercises. 3. ORTHOGONALITY. Perpendicular Vectors and Orthogonal Subspaces. Inner Products and Projections onto Lines. Least Squares Approximations. Orthogonal Bases, Orthogonal Matrices, and Gram-Schmidt Orthogonalization. The Fast Fourier Transform. Review and Preview. Review Exercises. 4. DETERMINANTS. Introduction. Properties of the Determinant. Formulas for the Determinant. Applications of Determinants. Review Exercises. 5. EIGENVALUES AND EIGENVECTORS. Introduction. Diagonalization of a Matrix. Difference Equations and the Powers Ak. Differential Equations and the Exponential eAt. Complex Matrices: Symmetric vs. Hermitian. Similarity Transformations. Review Exercises. 6. POSITIVE DEFINITE MATRICES. Minima, Maxima, and Saddle Points. Tests for Positive Definiteness. The Singular Value Decomposition. Minimum Principles. The Finite Element Method. 7. COMPUTATIONS WITH MATRICES. Introduction. The Norm and Condition Number. The Computation of Eigenvalues. Iterative Methods for Ax = b. 8. LINEAR PROGRAMMING AND GAME THEORY. Linear Inequalities. The Simplex Method. Primal and Dual Programs. Network Models. Game Theory. Appendix A: Computer Graphics. Appendix B: The Jordan Form. References. Solutions to Selected Exercises. Index.
520			_aRenowned professor and author Gilbert Strang demonstrates that linear algebra is a fascinating subject by showing both its beauty and value. While the mathematics is there, the effort is not all concentrated on proofs. Strang's emphasis is on understanding. He explains concepts, rather than deduces. This book is written in an informal and personal style and teaches real mathematics. The gears change in Chapter 2 as students reach the introduction of vector spaces. Throughout the book, the theory is motivated and reinforced by genuine applications, allowing pure mathematicians to teach applied mathematics.
650		0	_aMathematics
650		0	_aAlgebra
650		0	_aAlgebras, Linear
650		0	_vTextbooks.
906			_a7 _bcbc _corigcop _d3 _eepcn _f20 _gy-gencatlg
942			_cBK
942			_2ddc _n0
999			_c45041 _d45041