MIT
Season 4

32 Episodes

Season 4

Episodes

All »
  • 32 episodes
    32 episodes
    • s4e32Nonlinear optimization: algorithms and theory
    • s4e31Simplex method in linear programming
    • s4e30Network flows and combinatorics: max flow = min cut
    • s4e29Applications in signal and image processing: compression
    • s4e28Splines and orthogonal wavelets: Daubechies construction
    • s4e27Multiresolution, wavelet transform and scaling function
    • s4e26Filter banks and perfect reconstruction
    • s4e25Filters in the time and frequency domain
    • s4e24Discrete filters: lowpass and highpass
    • s4e23Fast fourier transform and circulant matrices
    • s4e22Fourier expansions and convolution
    • s4e21Spectral method: dynamic equations
    • s4e20Finite element method: equilibrium equations
    • s4e19Optimization and minimum principles: Euler equation
    • s4e18Finite difference methods: stability and convergence
    • s4e17Finite difference methods: equilibrium problems
    • s4e16Dynamic estimation: Kalman filter and square root filter
    • s4e15Numerical methods in estimation: recursive least squares and covari...
    • s4e14Numerical linear algebra: SVD and applications
    • s4e13Numerical linear algebra: orthogonalization and A = QR
    • s4e12Solutions of initial value problems: eigenfunctions
    • s4e11Initial value problems: wave equation and heat equation
    • s4e10Delta function and Green
    • s4e9Solutions of Laplace equation: complex variables
    • s4e8Applications to boundary value problems: Laplace equation
    • s4e7Discrete vs. continuous: differences and derivatives
    • s4e6Underlying theory: applied linear algebra
    • s4e5Applications to dynamics: eigenvalues of K, solution of Mu
    • s4e4Applications to linear estimation: least squares
    • s4e3Network applications: A = incidence matrix
    • s4e2One-dimensional applications: A = difference matrix
    • s4e1Positive definite matrices K = A