ODE Simulation Methods

4 credits

Orthogonality and norms. Reflection and rotation matrices. Solving systems of linear equations via LU and QR decompositions; least squares. Conditioning, sparsity, and parallelism. Iterative methods. Matrix subspaces. Eigen, Schur, and singular value decompositions. Pseudoinverses. Spectral representations, Fourier transforms, and the Dirac delta. Prerequisites: graduate standing.