Preface vii
1. Introduction and Review
1.1 Basic symbols
1.2 Quadratic forms and positive definite matrices
1.2.1 Quadratic forms
1.2.2 Problems involving quadratic forms
1.2.3 Positive definite matrix
1.2.4 Other methods to determine the positive definiteness
1.3 Theorems for eigenvalues of symmetric matrices
1.4 Complex inner product spaces
1.5 Hermitian, unitary, and normal matrices
1.6 Kronecker product and Kronecker sum
2. Norms and Perturbation Analysis
2.1 Vector norms
2.2 Matrix norms
2.3 Perturbation analysis for linear systems
2.4 Error on floating point numbers
3. Least Squares Problems
3.1 Solution of LS problems
3.2 Perturbation analysis for LS problems
3.3 Orthogonal transformations
3.3.1 Householder reflections
3.3.2 Givens rotations
3.4 An algorithm based on QR factorization
3.4.1 QR factorization
3.4.2 A practical algorithm for LS problems
4. Generalized Inverses
4.1 Moore-Penrose generalized inverse
4.2 Basic properties
4.3 Relation to LS problems
4.4 Other generalized inverses
5. Conjugate Gradient Method
5.1 Steepest descent method
5.1.1 Steepest descent method
5.1.2 Convergence rate
5.2 Conjugate gradientmethod
5.2.1 Conjugate gradient method
5.2.2 Basic properties
5.2.3 Practical CG method
5.3 Preconditioning technique
6. Optimal and Superoptimal Preconditioners
6.1 Introduction to optimal preconditioner
6.1.1 Circulantmatrix
6.1.2 Optimal preconditioner
6.2 Linear operator c_U
6.2.1 Algebraic properties
6.2.
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