Computational Science and Engineering I

Video Lectures

Displaying all 36 video lectures.
Lecture 1
Positive definite matrices K = A'CA
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Positive definite matrices K = A'CA
Lecture 2
One-dimensional applications: A = difference matrix
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One-dimensional applications: A = difference matrix
Lecture 3
Network applications: A = incidence matrix
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Network applications: A = incidence matrix
Lecture 4
Applications to linear estimation: least squares
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Applications to linear estimation: least squares
Lecture 5
Applications to dynamics: eigenvalues of K, solution of Mu'' + Ku = F(t)
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Applications to dynamics: eigenvalues of K, solution of Mu'' + Ku = F(t)
Lecture 6
Underlying theory: applied linear algebra
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Underlying theory: applied linear algebra
Lecture 7
Discrete vs. Continuous: Differences and Derivatives
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Discrete vs. Continuous: Differences and Derivatives
Lecture 8
Applications to boundary value problems: Laplace equation
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Applications to boundary value problems: Laplace equation
Lecture 9
Solutions of Laplace equation: complex variables
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Solutions of Laplace equation: complex variables
Lecture 10
Delta function and Green's function
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Delta function and Green's function
Lecture 11
Initial value problems: wave equation and heat equation
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Initial value problems: wave equation and heat equation
Lecture 12
Solutions of initial value problems: eigenfunctions
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Solutions of initial value problems: eigenfunctions
Lecture 13
Numerical linear algebra: orthogonalization and A = QR
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Numerical linear algebra: orthogonalization and A = QR
Lecture 14
Numerical linear algebra: SVD and applications
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Numerical linear algebra: SVD and applications
Lecture 15
Numerical methods in estimation: recursive least squares and covariance matrix
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Numerical methods in estimation: recursive least squares and covariance matrix
Lecture 16
Dynamic estimation: Kalman filter and square root filter
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Dynamic estimation: Kalman filter and square root filter
Lecture 17
Finite difference methods: equilibrium problems
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Finite difference methods: equilibrium problems
Lecture 18
Finite difference methods: stability and convergence
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Finite difference methods: stability and convergence
Lecture 19
Optimization and minimum principles: Euler equation
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Optimization and minimum principles: Euler equation
Lecture 20
Finite element method: equilibrium equations
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Finite element method: equilibrium equations
Lecture 21
Spectral method: dynamic equations
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Spectral method: dynamic equations
Lecture 22
Fourier expansions and convolution
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Fourier expansions and convolution
Lecture 23
Fast fourier transform and circulant matrices
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Fast fourier transform and circulant matrices
Lecture 24
Discrete filters: lowpass and highpass
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Discrete filters: lowpass and highpass
Lecture 25
Filters in the time and frequency domain
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Filters in the time and frequency domain
Lecture 26
Filter banks and perfect reconstruction
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Filter banks and perfect reconstruction
Lecture 27
Multiresolution, wavelet transform and scaling function
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Multiresolution, wavelet transform and scaling function
Lecture 28
Splines and orthogonal wavelets: Daubechies construction
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Splines and orthogonal wavelets: Daubechies construction
Lecture 29
Applications in signal and image processing: compression
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Applications in signal and image processing: compression
Lecture 30
Network flows and combinatorics: max flow = min cut
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Network flows and combinatorics: max flow = min cut
Lecture 31
Simplex method in linear programming
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Simplex method in linear programming
Lecture 32
Nonlinear optimization: algorithms and theory
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Nonlinear optimization: algorithms and theory
Lecture 33
Filters; Fourier integral transform (part 1)
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Filters; Fourier integral transform (part 1)
Lecture 34
Fourier integral transform (part 2)
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Fourier integral transform (part 2)
Lecture 35
Convolution equations: deconvolution; convolution in 2D
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Convolution equations: deconvolution; convolution in 2D
Lecture 36
Sampling Theorem
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Sampling Theorem