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Machine Learning
book

Machine Learning

by Sergios Theodoridis
April 2015
Intermediate to advanced content levelIntermediate to advanced
1062 pages
40h 35m
English
Academic Press
Content preview from Machine Learning
Chapter 4

Mean-Square Error Linear Estimation

Abstract

In this chapter, mean-square linear estimation is discussed and the normal equations are derived. The orthogonality theorem concerning random variables is introduced as an alternative for their derivation. Issues concerning complex random variables, such as widely-linear estimation and Wirtinger’s calculus are presented. Some typical applications of MSE, such as image deblurring, interference cancellation, system identification and channel equalization are defined. Issues related to the efficient solution of the normal equations in the context of linear filtering are discussed and the Levinson and lattice-ladder algorithms are derived. The Gauss-Markov theorem for MSE of linear models ...

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Publisher Resources

ISBN: 9780128015223