Neural network structure for emulating decision feedback equalisers

Graham W. Pulford*, Rodney A. Kennedy, Brian D.O. Anderson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The emulation of a tuned decision feedback equalizer operating on a noiseless finite impulse response channel by a feedforward multilayer neural network is considered. The similarity between the two structures is exploited to obtain tight bounds on the probability of error for the neural net as a function of the number of layers, using the theory of finite state Markov processes. A class of channels for which exact representation by a neural net of finite complexity is possible is established.

Original languageEnglish
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
PublisherPubl by IEEE
Pages1517-1520
Number of pages4
ISBN (Print)078030033
Publication statusPublished - 1991
EventProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 - Toronto, Ont, Can
Duration: 14 May 199117 May 1991

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume3
ISSN (Print)0736-7791

Conference

ConferenceProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91
CityToronto, Ont, Can
Period14/05/9117/05/91

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