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    Coursera - Computational Methods for Data Analysis

    Posted By: ParRus
    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis
    University of Washington with J. Nathan Kutz

    WEBRip | English | MP4 | 960 x 540 | AVC ~171 kbps | 30.920 fps
    AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 22:11:46 | 3.39 GB
    Genre: eLearning Video / Data Analysis

    Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences. Brief review of statistical methods and their computational implementation for studying time series analysis, spectral analysis, filtering methods, principal component analysis, orthogonal mode decomposition, and image processing and compression.
    Content:

    01 Computational Methods Course Overview
    02 Introduction to the Course
    03 MATLAB Usage in Course
    04 Week 1 - Lecture 1 - Time-Frequency Analysis - Fourier and Wavelet Transforms
    05 Week 1 - Lecture 2 - Radar Detection and Filtering
    06 Week 1 - Lecture 3 - Radar Detection and Averaging
    07 Week 2 - Lecture 4 - The Windowed Fourier Transform
    08 Week 2 - Lecture 5 - The Wavelet Transform
    09 Week 2 - Lecture 6 - The Wavelet Basis and Multi-Resolution Analysis
    10 Week 3 - Lecture 7 - Spectrograms and the Gabor transforms in MATLAB
    11 Week 3 - Lecture 8 - MATLAB Filter Design and Wavelet Toolboxes
    12 Week 4 - Lecture 9 - Image processing and analysis
    13 Week 4 - Lecture 10 - Linear Filtering for Image Denoising
    14 Week 4 - Lecture 11 - Diffusion and Image Processing
    15 Week 5 - Lecture 12 - Linear Algebra and the Singular Value Decomposition
    16 Week 5 - Lecture 13 - The SVD in Broader Context
    17 Week 5 - Lecture 14 - Principal Component Analysis
    18 Week 6 - Lecture 15 - Principal Component Analysis SVD diagonlization
    19 Week 6 - Lecture 16 - Principal Component and Proper Orthogonal Modes
    20 Week 7 - Lecture 17 - Independent Component Analysis
    21 Week 7 - Lecture 18 - Image Separation with the SVD
    22 Week 7 - Lecture 19 - Implementing an Image Separation Algorithm
    23 Week 8 - Lecture 20 - Image Recognition
    24 Week 8 - Lecture 21 - The SVD and linear discrimination analysis
    25 Week 8 - Lecture 22 - Implementing the catdog regognition algorithm
    26 Week 9 - Lecture 23 - Basics of Compressive Sensing
    27 Week 9 - Lecture 24 - Signal Reconstruction and Circumventing Nyquist
    28 Week 9 - Lecture 25 - Data Image Reconstruction from Sparse Sampling
    29 Week 10 - Lecture 26 - Dimensionality Reduction for Partial Differential Equations
    30 Week 10 - Lecture 27 - PDE dynamics in the right best basis
    31 Week 10 - Lecture 28 - Global normal forms of bifurcation structures in PDEs

    About the Instructor(s)

    J. Nathan Kutz
    PhD, Applied Mathematics, Northwestern University
    J. Nathan Kutz specializes in a unified approach to applied mathematics including modeling, computation and analysis. His current focus is phenomena in dimensionality reduction and data-analysis techniques for complex systems. This includes work in laser dynamics and modelocking in fiber lasers, neuro-sensory systems and theoretical neuroscience, and gesture recognition algorithms for portable electronic devices. Kutz has authored numerous scientific articles on these subjects as well as segments of books devoted to his area of expertise.

    also You can watch my other last: Coursera-posts

    General
    Complete name : 01_W7_L19_P1_-_Algorithm_Overview_of_ICA_and_Image_Separation_12-47.mp4
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    Screenshots

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

    Coursera - Computational Methods for Data Analysis

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    Coursera - Computational Methods for Data Analysis