Matrix Analysis for Scientists and Engineers

Preface 1. Introduction and review 2. Vector spaces 3. Linear transformations 4. Introduction to the Moore-Penrose pseudoinverse 5. Introduction to the singular value decomposition 6. Linear equations 7. Projections, inner product spaces, and norms 8. Linear least squares problems 9. Eigenvalues and eigenvectors 10. Canonical forms 11. Linear differential and difference equations 12. Generalized eigenvalue problems 13. Kronecker products Bibliography Index.