A particle swarm optimization based support vector machine for digital communication equalizers

The support vector machine (SVM) is a powerful tool for solving problems with high dimensional, nonlinearly, and is of excellent performance for channel equalization in communication systems. In this study, we propose PSO-SVM as channel equalization. To reconstruct the signal that has the inter symbol interference (ISI) and white Gaussian noise which in high speed communications environments. The SVM parameters will affect the identification of the result. Therefore, we use particle swarm optimization (PSO) to find the suit parameters in SVM. The PSO-SVM to realize the Bayesian equalization solution can be achieved efficiently.