Performance of swarm based optimization techniques for designing digital FIR filter: A comparative study
Ila Sharma, B. Kuldeep, Anil Kumar, Vineet Kumar Singh · Engineering Science and Technology an International Journal · 2016
In this paper, a linear phase FIR filter is designed through recently proposed nature inspired optimization algorithm known as Cuckoo search ( CS ). A comparative study of Cuckoo search ( CS ), particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization methods in the field of linear phase FIR filter design is also presented. For this purpose, an improved L 1 weighted error function is formulated in frequency domain, and minimized through CS , PSO and ABC respectively. The error or objective function has a controlling parameter wt which controls the amount of ripple in the desired band of frequency. The performance of FIR filter is examined through three key parameters; Maximum Pass Band Ripple ( MPR ), Maximum Stopband Ripple ( MSR ) and Stopband Attenuation ( A s ). Comparative study and the simulation results reveal that the designed filter with CS gives better performance in terms of Maximum Stopband Ripple ( MSR ), and Stopband Attenuation ( A s ) for low order filter design, and for higher order it also gives better performance in term of Maximum Passband Ripple ( MPR ). Superiority of the proposed technique is also shown through comparison with other recently proposed methods.