THE SINGULAR VALUE DECOMPOSITION (SVD): Perhaps the most important concept in this course, an introduction to the SVD is given and its mathematical foundations.
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SVD
PRINCIPAL COMPONENT ANALYSIS (PCA): The SVD algorithm is used to produce the dominant correlated mode structures in a data matrix.
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PCA VAR COV
PCA FOR FACE RECOGNITION: We demonstrate the power of the SVD/PCA framework on the computer vision problem of face recognition.
MATLAB COMMANDS
RESHAPE IMRESIZE FLIPUD IMSHOW RGB2GRAY
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