ADAPTIVE EQUALIZER USING SELF-GENERATING RADIAL BASIS FUNCTION NETWORK

In digital communication systems, a linear transversal equalizer was a pplied to signal equalization. But because of the nonlinearity of the equalization problem, it was desirable to incorporate some nonlinearit y in the adaptive equalizer structure. We considered the application o f the radial basis function (RBF) network to the adaptive equalizer an d compared the performance of the equalizer using an RBF network betwe en the maximum absolute error (MAE) selection method and the orthogona l least squares (OLS) method as a learning procedure. By comparing the MAE method with the OLS method, we show that the MAE method can achie ve a more efficient performance in terms of bit error rate with fewer basis functions than the OLS method. (C) 1997 John Wiley & Sons, Inc.