Heuristic optimization techniques for the design of band stop digital FIR filter: A comparison

For the design of finite impulse response (FIR) filter a lot of research has been conducted which involves multi-objective, multi-modal optimization techniques that can be used to calculate the filter impulse response coefficients and try to get the ideal frequency response characteristics. This paper presents evolutionary algorithms for the design of digital FIR filter. Particle swarm optimization (PSO) and differential evolution (DE) algorithms have been applied. Comparison has been done on the basis of magnitude error, ripple magnitudes of both pass band and stop band and maximum stop band attenuation. DE appears to be more promising method for the design of linear phase digital FIR filter especially in the dynamic environment where filter coefficients have to be adapted and convergence speed is of major concern.