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Least Squares with Examples in Signal Processing 1

TLDR
In these notes, least squares is illustrated by applying it to several basic problems in signal processing, e.g. singular value decomposition, or the pseudo-inverse.
Abstract
Ivan Selesnick March 7, 2013 NYU-Poly These notes address (approximate) solutions to linear equations by least squares. We deal with the ‘easy’ case wherein the system matrix is full rank. If the system matrix is rank deficient, then other methods are needed, e.g., QR decomposition, singular value decomposition, or the pseudo-inverse, [2, 3]. In these notes, least squares is illustrated by applying it to several basic problems in signal processing:

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References
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Book

Solving least squares problems

TL;DR: Since the lm function provides a lot of features it is rather complicated so it is going to instead use the function lsfit as a model, which computes only the coefficient estimates and the residuals.
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Error control and concealment for video communication: a review

TL;DR: In this paper, a review of error control and concealment in video communication is presented, which are described in three categories according to the roles that the encoder and decoder play in the underlying approaches.
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Numerical Recipes in C++: The Art of Scientific Computing (2nd edn)1 Numerical Recipes Example Book (C++) (2nd edn)2 Numerical Recipes Multi-Language Code CD ROM with LINUX or UNIX Single-Screen License Revised Version3

TL;DR: Anyone involved in scientific computing ought to have a copy of at least one version of Numerical Recipes, and there also ought to be copies in every library.
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