title: A clustering technique for digital communications channel equalization using radial basis function networks.
abstract: 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.
authors.affiliation: Dept. of Electr. Eng., Edinburgh Univ.
authors.forename: S
authors.initials: S
authors.lastname: Chen
authors.forename: B
authors.initials: B
authors.lastname: Mulgrew
authors.forename: P M
authors.initials: PM
authors.lastname: Grant