Optimum lag and subset selection for radial basis function equaliser

Chng, E. S., Mulgrew, B., Chen, S. and Gibson, G. (1995) Optimum lag and subset selection for radial basis function equaliser. 5th IEEE Workshop on Neural Networks for Signal Processing, Cambridge, United States. 31 Aug - 02 Sep 1995. pp. 593-602 .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper examines the application of the radial basis function (RBF) network to the modelling of the Bayesian equaliser. In particular, we study the effects of delay order d on decision boundary and
attainable bit error rate (BFR) performance. To determine the optimum delay parameter for minimum BER performance, a simple BER estimator is proposed. The implementation complexity of the RBF network grows exponentially with respect to the number of input nodes. As such, the full implementation of the RBF network to realise the Bayesian solution may not be feasible. To reduce some of the implementation complexity, we propose an algorithm to perform subset model selection. Our
results indicate that it is possible to reduce model size without, significant degradation in BER performance.

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Published date: 1995

Additional Information: 5th IEEE Workshop on Neural Networks for Signal Processing (Cambridge, USA), Aug. 31-Sept. 2, 1995. Event Dates: Aug. 31-Sept. 2, 1995 Organisation: IEEE Signal Processing Society

Venue - Dates: 5th IEEE Workshop on Neural Networks for Signal Processing, Cambridge, United States, 1995-08-31 - 1995-09-02

Organisations: Southampton Wireless Group

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