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Generalized least squares lattice algorithm and its application to decision feedback equalization

Authors: null Fuyun Ling; J. Proakis;

Generalized least squares lattice algorithm and its application to decision feedback equalization

Abstract

A generalized least squares lattice algorithm (GLSLA), which is appropriate for multi-channel adaptive filtering and estimation, is presented. This algorithm has all the advantages of a conventional least-squares (LS) lattice algorithm, such as computational efficiency, numerical stability, and the property that successive stages are decoupled. Besides these advantages, it also has the flexibility that the number of stages in each channel may be different. This property does not exist in the conventional LS lattice algorithms. As an application, a decision feedback equalizer (DFE) with different numbers of feedforward and feedback stages is proposed and implemented using the GLSLA. Some results obtained from a computer simulation of the algorithm are also presented.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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