Abstract

Novelty of PSO is the techniques of parameter improvement. Using many “strategy principles” for the PSO is important for its convergence performance and the optimisation job. In the proposed work, we applied PSO and its advanced form trained with our proposed algorithm for channel equalization. Since particle swarm optimization is matured in the literature ,we apply PSO in its optimized structure trained with radial basis function Artificial Neural Network (ANN). Therefore, this work introduces most favourable design of RBFNN equalizers using OPSO. We treat equalization problem as a classification problem. We assessed a set of fitness functions of modified form of PSO and analysed with it to the presentation of existing PSO .

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