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Harvard AM205 video 4.11 - Penalty methods and linear programming
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Harvard Applied Math 205 is a graduate-level course on scientific computing and numerical methods. This video continues the survey of different optimization methods. The first half of the video discusses penalty methods, which allow constrained optimization problems to be converted into unconstrained ones. The second half shows an example of linear programming, an important subfield of optimization.
Harvard AM205 video 3.11 - Runge–Kutta methods
Harvard AM205 video 3.12 - ODE error estimation
Harvard AM205 video 1.4 - The Lebesgue constant
Harvard AM205 video 0.4 - Finite-precision arithmetic
Harvard AM205 video 2.10 - Givens rotations
Harvard AM205 video 2.4 - LU factorization
Harvard AM205 video 3.10 - ODE stability
Harvard AM205 video 3.21 - Parabolic PDEs: the heat equation
Harvard AM205 video 3.8 - One-step integration methods
Harvard AM205 video 1.8 - Nonlinear least squares
Harvard AM205 video 3.5 - Finite-difference approximations
Harvard AM205 video 0.2 - Sources of error
Harvard AM205 video 3.6 - Differentiation matrices
Harvard AM205 video 3.13 - Stiff ODE systems
Harvard AM205 video 4.8 - Steepest descent and Newton methods for optimization
Harvard AM205 video 1.6 - Linear least squares
Harvard AM205 video 3.18 - CFL condition & upwinding
Harvard AM205 video 3.14 - Multistep methods
4a. Newton-artige Verfahren: Das Newton-Verfahren
Harvard AM205 video 2.8 - Gram–Schmidt orthogonalization
Harvard AM205 video 2.5 - LU pivoting and Cholesky factorization
Harvard AM205 video 2.9 - Householder triangularization
Harvard AM205 video 2.7 - QR decomposition
Harvard AM205 video 3.22 - Elliptic PDEs: the Poisson equation
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