Modified Form of PSO and Its Variation in Channel Equalization

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 .

An Efficient Method of Group Delay Equalization for Digital IIR Filters

The paper presents the equalization problem of non-linear phase response of digital IIR type filters. An improved analytical method of designing a low-order equalizer is presented. The proposed approach is compared with the original method. The genetic algorithm is presented as an iterative method of optimization. The vector and matrix representation of the all-pass equalizer are shown and introduced to the algorithm. The results are compared with the analytical method. In this paper we have also proposed the use of an aging factor and setting the initial population of the genetic algorithm around the solution provided by the analytical methodology