Design of Optimal FIR Digital Filter by Swarm Optimization Technique

Finite Impulse Response (FIR) digital filters are widely used in digital signal processing and other engineering because of their strict stability and linear phase. Aiming at the problems of low accuracy and weak optimization ability of traditional method to design digital filter, the newly proposed Grey Wolf Optimization (GWO) algorithm is used in this paper to design a linear-phase FIR filter to obtain the optimal transition-band sample value in the frequency sampling method to obtain the minimum stop-band attenuation, so as to improve the performance of the filter. And improved by embedding Levy Flight (LF), which is the modified Levy-embedded GWO (LGWO). Finally, the performance of traditional frequency sampling methods and optimization algorithms GWO and LGWO are compared. When the number of sampling points is 65 and 97, the stopband attenuation of LGWO is improved by 0.2029 dB and 0.2454 dB respectively compared with GWO algorithm. The better performance of LGWO is shown in the results.