Applied Linear Algebra / 1: |
Four special matrices / 1.1: |
Differences, derivatives, and boundary conditions / 1.2: |
Elimination leads to K = LDL^T / 1.3: |
Inverses and delta functions / 1.4: |
Eigenvalues and eigenvectors / 1.5: |
Positive definite matrices / 1.6: |
Numerical linear algebra: LU, QR, SVD / 1.7: |
Best basis from the SVD / 1.8: |
A Framework for Applied Mathematics / 2: |
Equilibrium and the stiffness matrix / 2.1: |
Oscillation by Newton's law / 2.2: |
Least squares for rectangular matrices / 2.3: |
Graph models and Kirchhoff's laws / 2.4: |
Networks and transfer functions / 2.5: |
Nonlinear problems / 2.6: |
Structures in equilibrium / 2.7: |
Covariances and recursive least squares / 2.8: |
Graph cuts and gene clustering / 2.9: |
Boundary Value Problems / 3: |
Differential equations of equilibrium / 3.1: |
Cubic splines and fourth order equations / 3.2: |
Gradient and divergence / 3.3: |
Laplace's equation / 3.4: |
Finite differences and fast Poisson solvers / 3.5: |
The finite element method / 3.6: |
Elasticity and solid mechanics / 3.7: |
Fourier Series and Integrals / 4: |
Fourier series for periodic functions / 4.1: |
Chebyshev, Legendre, and Bessel / 4.2: |
The discrete Fourier transform and the FFT / 4.3: |
Convolution and signal processing / 4.4: |
Fourier integrals / 4.5: |
Deconvolution and integral equations / 4.6: |
Wavelets and signal processing / 4.7: |
Analytic Functions / 5: |
Taylor series and complex integration / 5.1: |
Famous functions and great theorems / 5.2: |
The Laplace transform and z-transform / 5.3: |
Spectral methods of exponential accuracy / 5.4: |
Initial Value Problems / 6: |
Introduction / 6.1: |
Finite difference methods for ODEs / 6.2: |
Accuracy and stability for u_t = c u_x / 6.3: |
The wave equation and staggered leapfrog / 6.4: |
Diffusion, convection, and finance / 6.5: |
Nonlinear flow and conservation laws / 6.6: |
Fluid mechanics and Navier-Stokes / 6.7: |
Level sets and fast marching / 6.8: |
Solving Large Systems / 7: |
Elimination with reordering / 7.1: |
Iterative methods / 7.2: |
Multigrid methods / 7.3: |
Conjugate gradients and Krylov subspaces / 7.4: |
Optimization and Minimum Principles / 8: |
Two fundamental examples / 8.1: |
Regularized least squares / 8.2: |
Calculus of variations / 8.3: |
Errors in projections and eigenvalues / 8.4: |
The Saddle Point Stokes problem / 8.5: |
Linear programming and duality / 8.6: |
Adjoint methods in design / 8.7: |
Applied Linear Algebra / 1: |
Four special matrices / 1.1: |
Differences, derivatives, and boundary conditions / 1.2: |