Matrix Analysis and Applied Linear AlgebraSIAM, 1 jan 2000 - 730 pagina's Matrix Analysis and Applied Linear Algebra is an honest math text that circumvents the traditional definition-theorem-proof format that has bored students in the past. Meyer uses a fresh approach to introduce a variety of problems and examples ranging from the elementary to the challenging and from simple applications to discovery problems. The focus on applications is a big difference between this book and others. Meyer's book is more rigorous and goes into more depth than some. He includes some of the more contemporary topics of applied linear algebra which are not normally found in undergraduate textbooks. Modern concepts and notation are used to introduce the various aspects of linear equations, leading readers easily to numerical computations and applications. The theoretical developments are always accompanied with examples, which are worked out in detail. Each section ends with a large number of carefully chosen exercises from which the students can gain further insight. |
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Matrix Analysis and Applied Linear Algebra Book and Solutions Manual Carl Meyer Geen voorbeeld beschikbaar - 2000 |
Veelvoorkomende woorden en zinsdelen
3-digit alg multA algebra algorithm An×n arithmetic associated back substitution basic columns coefficient compute Consequently consider converges defined definition Determine diagonalizable dimN eigenpair eigenvalues eigenvectors elementary equations equivalent Example Exercises for section exercises in section exists Explain fact Figure find first Fourier function Gaussian elimination given Gram–Schmidt implies independent set inequality inner product inner-product space insures inverse irreducible Jordan block Jordan form left-hand linear operator linear system linearly independent LU factorization matrix norm multiplication nilpotent nilpotent matrix nodes nonnegative nonsingular matrix nonzero orthogonal matrix orthogonal projector orthonormal basis partial pivoting permutation Perron vector positive Problem Proof properties prove QR factorization rank reduced result rotation row echelon form scalar singular values Solutions for exercises solve spanning set spectral subspaces Suppose symmetric theorem triangular unitary vector space verify write zero