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A Compressed Overview of Sparsity
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Linear Algebra
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- 1 A Compressed Overview of Sparsity
- 2 2016 AIAA AVIATION Forum: Flow Control - Steve Brunton
- 3 Singular Value Decomposition (SVD): Overview
- 4 Singular Value Decomposition (SVD): Mathematical Overview
- 5 Singular Value Decomposition (SVD): Matrix Approximation
- 6 Singular Value Decomposition (SVD): Dominant Correlations
- 7 The Frobenius Norm for Matrices
- 8 SVD Method of Snapshots
- 9 Matrix Completion and the Netflix Prize
- 10 Unitary Transformations
- 11 Linear Systems of Equations, Least Squares Regression, Pseudoinverse
- 12 Least Squares Regression and the SVD
- 13 Linear Systems of Equations
- 14 Linear Regression
- 15 Principal Component Analysis (PCA)
- 16 SVD and Optimal Truncation
- 17 SVD: Image Compression [Matlab]
- 18 SVD: Image Compression [Python]
- 19 Unitary Transformations and the SVD [Matlab]
- 20 Unitary Transformations and the SVD [Python]
- 21 Linear Regression 1 [Matlab]
- 22 Linear Regression 2 [Matlab]
- 23 Linear Regression 1 [Python]
- 24 Linear Regression 2 [Python]
- 25 Linear Regression 3 [Python]
- 26 SVD and Alignment: A Cautionary Tale
- 27 Principal Component Analysis (PCA) [Matlab]
- 28 Principal Component Analysis (PCA) 1 [Python]
- 29 Principal Component Analysis (PCA) 2 [Python]
- 30 SVD: Eigenfaces 1 [Matlab]
- 31 SVD: Eigenfaces 2 [Matlab]
- 32 SVD: Eigenfaces 3 [Matlab]
- 33 SVD: Eigenfaces 4 [Matlab]
- 34 SVD: Eigen Action Heros [Matlab]
- 35 SVD: Eigenfaces 3 [Python]
- 36 SVD: Eigenfaces 2 [Python]
- 37 SVD: Eigenfaces 1 [Python]
- 38 SVD: Optimal Truncation [Matlab]
- 39 SVD: Optimal Truncation [Python]
- 40 SVD: Importance of Alignment [Python]
- 41 SVD: Importance of Alignment [Matlab]
- 42 Randomized SVD Code [Matlab]
- 43 Randomized SVD Code [Python]
- 44 Randomized Singular Value Decomposition (SVD)
- 45 Randomized SVD: Power Iterations and Oversampling
- 46 Fourier Analysis: Overview
- 47 Fourier Series: Part 1
- 48 Fourier Series: Part 2
- 49 Inner Products in Hilbert Space
- 50 Complex Fourier Series
- 51 Fourier Series [Matlab]
- 52 Fourier Series [Python]
- 53 Fourier Series and Gibbs Phenomena [Matlab]
- 54 Fourier Series and Gibbs Phenomena [Python]
- 55 The Fourier Transform
- 56 The Fourier Transform and Derivatives
- 57 The Fourier Transform and Convolution Integrals
- 58 Parseval's Theorem
- 59 Solving the Heat Equation with the Fourier Transform
- 60 The Discrete Fourier Transform (DFT)
- 61 Computing the DFT Matrix
- 62 The Fast Fourier Transform (FFT)
- 63 The Fast Fourier Transform Algorithm
- 64 Denoising Data with FFT [Matlab]
- 65 Denoising Data with FFT [Python]
- 66 Computing Derivatives with FFT [Matlab]
- 67 Computing Derivatives with FFT [Python]
- 68 Solving PDEs with the FFT [Matlab]
- 69 Solving PDEs with the FFT [Python]
- 70 Why images are compressible: The Vastness of Image Space
- 71 What is Sparsity?
- 72 Sparsity and Parsimonious Models: Everything should be made as simple as possible, but no simpler
- 73 Compressed Sensing: Overview
- 74 Compressed Sensing: Mathematical Formulation
- 75 Compressed Sensing: When It Works
- 76 Sparsity and the L1 Norm
- 77 Solving PDEs with the FFT, Part 2 [Matlab]
- 78 Solving PDEs with the FFT, Part 2 [Python]
- 79 The Spectrogram and the Gabor Transform
- 80 Spectrogram Examples [Matlab]
- 81 Spectrogram Examples [Python]
- 82 Uncertainty Principles and the Fourier Transform
- 83 Wavelets and Multiresolution Analysis
- 84 Image Compression and the FFT
- 85 Sparse Sensor Placement Optimization for Reconstruction
- 86 Sparse Sensor Placement Optimization for Classification
- 87 Sparse Representation (for classification) with examples!
- 88 Image Compression with Wavelets (Examples in Python)
- 89 Image Compression with the FFT (Examples in Matlab)
- 90 Image Compression and Wavelets (Examples in Matlab)
- 91 Image Compression and the FFT (Examples in Python)
- 92 Beating Nyquist with Compressed Sensing, part 2
- 93 Underdetermined systems and compressed sensing [Matlab]
- 94 Underdetermined systems and compressed sensing [Python]
- 95 Beating Nyquist with Compressed Sensing
- 96 Robust Regression with the L1 Norm
- 97 Robust Regression with the L1 Norm [Matlab]
- 98 Robust Regression with the L1 Norm [Python]
- 99 Beating Nyquist with Compressed Sensing, in Python
- 100 PySINDy: A Python Library for Model Discovery
- 101 The Laplace Transform: A Generalized Fourier Transform
- 102 Laplace Transforms and Differential Equations
- 103 Laplace Transform Examples
- 104 Sparsity and Compression: An Overview
- 105 Data-Driven Resolvent Analysis
