A clustering technique for digital communications channel equalization using radial basis function networks

The application of a radial basis function network to digital communications channel equalization is examined. It is shown that the radial basis function network has an identical structure to the optimal Bayesian symbol-decision equalizer solution and, therefore, can be employed to implement the Bay...

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Vydáno v:IEEE transactions on neural networks Ročník 4; číslo 4; s. 570 - 590
Hlavní autoři: Chen, S., Mulgrew, B., Grant, P.M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.07.1993
Institute of Electrical and Electronics Engineers
Témata:
Adaptive equalizers
Adaptive filters
Applied sciences
Bayesian methods
Communication systems
Data communication
Detection, estimation, filtering, equalization, prediction
Digital communication
Exact sciences and technology
Information, signal and communications theory
Maximum likelihood detection
Maximum likelihood estimation
Nonlinear filters
Radial basis function networks
Signal and communications theory
Signal, noise
Telecommunications and information theory
Computer simulation
Telecommunication network
Transmission channel
Data transmission
Equalizer
Neural network
Equalization
Algorithm
Bayes decision
ISSN:1045-9227
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Shrnutí:The application of a radial basis function network to digital communications channel equalization is examined. It is shown that the radial basis function network has an identical structure to the optimal Bayesian symbol-decision equalizer solution and, therefore, can be employed to implement the Bayesian equalizer. The training of a radial basis function network to realize the Bayesian equalization solution can be achieved efficiently using a simple and robust supervised clustering algorithm. During data transmission a decision-directed version of the clustering algorithm enables the radial basis function network to track a slowly time-varying environment. Moreover, the clustering scheme provides an automatic compensation for nonlinear channel and equipment distortion. Computer simulations are included to illustrate the analytical results.< >
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ISSN:1045-9227
DOI:10.1109/72.238312