Maximum margin equalizers trained with the Adatron algorithm
Signal Processing
Performance Comparison of Several Non-Linear Equalizers in the Context of Mobile Telecommunications
Information Systems Frontiers
Non-linear channel equalization using adaptive MPNN
Applied Soft Computing
Reduced RBF centers based multi-user detection in DS-CDMA systems
ICHIT'06 Proceedings of the 1st international conference on Advances in hybrid information technology
Channel equalization using neural networks: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Theoretical derivation of minimum mean square error of RBF based equalizer
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
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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