Comparative study of heuristic search algorithm in digital FIR filter design

The group intelligent algorithm is random optimization tool following the group behavior in the nature biological structure, which is a powerful tool for many optimization issues. This paper first models the digital filter design a constrained optimization problem with non-uniform frequency sampling, and then contrasts three kinds of intelligent algorithms to solve the problem. The computer simulation and the statistical analysis of the results suggest that digital filter designed by the artificial bee colony algorithm is better than those of genetic algorithm and the particle swarm optimization algorithm in terms of the convergence and the iterative times and filter.