IEEE Transactions on Neural Networks · 1999 · 29 citations · 12 references
EngineeringComputer EngineeringComputer ScienceOptimizationPerformance-based DesignSimulation-based DesignDigital Signal ProcessingSmall-signal AnalysisEqualizationRadial Basis Function NetworksSimulation Studies
A radial basis function (RBF) equalizer design process has been developed in which the number of basis function centers used is substantially fewer than conventionally required. The reduction of centers is accomplished in two-steps. First an algorithm is used to select a reduced set of centers that lie close to the decision boundary. Then the centers in this reduced set are grouped, and an average position is chosen to represent each group. Channel order and delay, which are determining factors in setting the initial number of centers, are estimated from regression analysis. In simulation studies, an RBF equalizer with more than 2000-to-1 reduction in centers performed as well as the RBF equalizer without reduction in centers, and better than a conventional linear equalizer.
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