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Blind Equalization in Neural Networks
book

Blind Equalization in Neural Networks

by Liyi Zhang, Tsinghua University Tsinghua University Press
December 2017
Intermediate to advanced content levelIntermediate to advanced
268 pages
7h 59m
English
De Gruyter
Content preview from Blind Equalization in Neural Networks

In eq. (2.78), R = E[Y(n)YT(n)] is the autocorrelation matrix of the equalizer input sequence and P = E[x˜(n)YT(n)] is the correlation matrix. The MSE is generally composed of two parts, such as theoretical error and excess MSE.

2.5.7.1The theoretical error

The theoretical error refers to the error produced by adopting finite length transversal filter to replace the infinite length transversal filter.

For the infinite filter, if the noise superimposed in channel is ignored, then

x˜(n)=WT(n)Y(n)=i=+wi(n)y(ni)=i=+j=+wi(n)hj(n)x(nij)=l=+x(n1)i=+wi(n)hli(n)=l=+δl(n)x(nl)=x(n)(2.79)

and required

i=+wi(n)hli(n)=δl(n)

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Publisher Resources

ISBN: 9783110449679