FIR Digital Filters Design: Particle Swarm Optimization Utilizing LMS and Minimax Strategies

In this paper, a FIR filter is designed using particle swarm optimization (PSO). Two design cases are organized as follows: low-pass and band-pass filter. In addition, the authors examine the utility of various error norms such as least mean squares (LMS) and minimax, and their impact on convergence behavior and optimal resultant frequency response. The effect of different population and iteration in PSO based FIR filter design is investigated, too. Examples of 1-D FIR filters are given using the above methodologies to illustrate the usefulness and efficiency of the proposed techniques.