Optimization of Control Parameters of Differential Evolution Technique for the Design of FIR Pulse-shaping Filter in QPSK Modulated System

Date Added: Oct 2011
Format: PDF

Signal Processing in modern era, involves rigorous applications of various evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) for the optimized design of aerodynamic shape, automated mirror, digital filter, computational intelligence etc. DE has been judged to be quite effective in designing different types of digital filter with good convergence behavior. The performance of the DE optimization technique could be improved to a further extent if the values of the two control parameters namely "Weighting Factor" and "Crossover Probability", be chosen properly.