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Linear Algebra, Matrix Theory and Applications
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Linear Algebra, Matrix Theory and Applications gives insights into the various aspects related to the matrices including the concepts on vector spaces, least square regression, determinants, eigen values, eigen vectors, positive definite matrices, singular value decomposition and teaches the readers the methods of computation in matrices.
This book also discusses about Reduced triangular form of polynomial, Gaussian Elimination-based correlation analysis, Shift-invert diagonalization of spin chains, Fast matrix multiplication, Finding the pth root of principal matrix and Quasi-rational canonical form of a matrix.
This book also discusses about Reduced triangular form of polynomial, Gaussian Elimination-based correlation analysis, Shift-invert diagonalization of spin chains, Fast matrix multiplication, Finding the pth root of principal matrix and Quasi-rational canonical form of a matrix.
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