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The Theory of Matrices With Applications Lancaster Tismenetsky Hardback 2e

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Product Description

The Theory of Matrices

With Applications

Peter Lancaster (Author), Miron Tismenetsky (Author)

9780124355606

Hardback, published 24 May 1985

586 pages

22.9 x 15.2 x 3.3 cm, 0.81 kg

In this book the authors try to bridge the gap between the treatments of matrix theory and linear algebra. It is aimed at graduate and advanced undergraduate students seeking a foundation in mathematics, computer science, or engineering. It will also be useful as a reference book for those working on matrices and linear algebra for use in their scientific work.

Maxtrix Algebra. Determinants, Inverse Matrices, and Rank. Linear, Euclidean, and Unitary Spaces. Linear Transformations and Matrices. Linear Transformations in Unitary Spaces and Simple Matrices. The Jordan Canonical Form: A Geometric Approach. Matrix Polynomials and Normal Forms. The Variational Method. Functions of Matrices. Norms and Bounds for Eigenvalues. Perturbation Theory. Linear Matrix Equations and Generalize]

The Theory of Matrices With Applications Lancaster Tismenetsky Hardback 2e

The Theory of Matrices

With Applications

Peter Lancaster (Author), Miron Tismenetsky (Author)

9780124355606

Hardback, published 24 May 1985

586 pages

22.9 x 15.2 x 3.3 cm, 0.81 kg

In this book the authors try to bridge the gap between the treatments of matrix theory and linear algebra. It is aimed at graduate and advanced undergraduate students seeking a foundation in mathematics, computer science, or engineering. It will also be useful as a reference book for those working on matrices and linear algebra for use in their scientific work.

Maxtrix Algebra. Determinants, Inverse Matrices, and Rank. Linear, Euclidean, and Unitary Spaces. Linear Transformations and Matrices. Linear Transformations in Unitary Spaces and Simple Matrices. The Jordan Canonical Form: A Geometric Approach. Matrix Polynomials and Normal Forms. The Variational Method. Functions of Matrices. Norms and Bounds for Eigenvalues. Perturbation Theory. Linear Matrix Equations and Generalize]

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