Topics:

1. Eigenvalues and eigenvectors of matrices, invariant subspaces, characteristic polynomial, diagonalizable matrices, minimal polynomial, Schur form, Cayley-Hamilton Theorem, localization of eigenvalues, Gerschgorin's Theorem.

2. Unitary, Hermitian and skew-Hermitian matrices. Cayley transform. Normal matrices and the Spectral Theorem. The field of values and the numerical radius of a matrix. Bendixson's Theorem.

3. The Singular Value Decomposition. Matrix norms: spectral norm and Frobenius norm. Solution to matrix nearness problems. Applications to signal processing and information retrieval.

4. Moore-Penrose pseudoinverse. Applications to the solution of under- and over-determined systems of linear equations. Other generalized inverses. Applications to data fitting (least-squares approximation).

5. Jordan canonical form. An algorithmic proof. Powers of matrices. Matrix functions. Applications to systems of differential equations.

6. Bilinear and quadratic forms. Hermitian forms. Congruence. Sylvester's Law of Inertia. Rayleigh's principle. Courant-Fischer Theorem. Positive definite and semidefinite matrices. Applications to statistics (covariance matrices) and numerical analysis (PDEs).

7. Nonnegative matrices. The spectral radius. Positive matrices. Directed graphs. Nonnegative irreducible matrices. Perron-Frobenius Theorem. M-matrices. Applications to probability theory (Markov chains), network science (centrality and communicability), and information retrieval (Google's PageRank algorithm).

Textbook:

R. A. Horn and C. R. Johnson, **Matrix Analysis**. Second Edition,
Cambridge University Press, 2013.

Additional suggested readings:

H. Shapiro, **Linear Algebra and Matrices: Topics for a Second Course**. American Mathematical
Society, 2015.

C. D. Meyer, **Matrix Analysis and Applied Linear Algebra**, Society for Industrial and Applied Mathematics,
2000.

R. A. Horn and C. R. Johnson, **Topics in Matrix Analysis**,
Cambridge University Press (1991; 1994).

A. Berman and R. J. Plemmons, **Nonnegative Matrices in the
Mathematical Sciences**, Academic Press (1979); reprinted by
SIAM, 1994.

Last updated January 5, 2017.