Applied linear algebra
Matrix algebra; Some simple applications of matrices; Simultaneous linear equations and elementary operations. Vectors and cector spaces; Matrices and linear transformations; Practical solution of systems of equations; Linear programming; Eigenvalues and eigenvectors: an overview; Unitary transformation, eigensystems and applications; Similarity transformations, eigensystems, and applications; Quadratic forms and variational principles.
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Some Simple Applications of Matrices
Simultaneous Linear Equations
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applied arbitrary augmented matrix basic feasible vector basis Chapter compute consider converges corresponding deduce defined denote described diagonal elements diagonal matrix dimension dual eigen eigensystem eigenvalues eigenvectors associated equal equations Ax equivalent exact range space example EXERCISE exists Gauss elimination geometrical given gives hence hermitian matrix inner product invariant subspaces inverse Key Theorem 8.3 linear combination linear equations linear program linear transformation linearly independent set m x n matrix notation maximize multiplicity n x n matrix nonsingular nonzero norm normal null space optimal orthogonal perturbed pivot polynomial positive definite precisely problem proof Prove QR decomposition quadratic form rank Rayleigh quotient reduce result right-inverse row-echelon form satisfy scalar Section set of equations set of vectors similarity transformation simplex method singular singular-value decomposition solve spans square matrix Suppose symmetric matrix tableau tion unitary matrix unknowns upper triangular vector space Verify zero