Design and Performance Analysis of Digital FIR Filter based on PSO Algorithm using MATLAB

Filter has an important role in digital signal processing which is basically used in the applications for the minimization of distortion in the system. For transmitting and receiving of unaffected signal, the designing of filters is required, those eliminate the distortion from the desired signal efficiently and no noise be added in signal processing itself. The various important uses of the digital filter has strained the researchers, engineers, and scientists to design such filters with spontaneous, capable, rapid techniques by the usage of advanced technology with intelligent tools. F.I.R filters are more favored over IIR filters due to linearity in the phase response and frequency stability. Various windowing functions are existing i.e Hamming, Rectangular, Blackman, Hanning, Flat-top etc but the Kaiser-window function is more advantageous due to the variable parameters to control width of main lobe and to attenuate side band ripples. Various optimization algorithms may be utilized and the researchers analyze advantages and disadvantages. Particle Swarm Optimization algorithm(P.S.O) is become a known malleable method based on Swarm-Intelligence, mainly particle’s population in search space. P.S.O enhance the features of result by renovate the position and velocity of swarms. Optimized group of filter coefficients have been generated using P.S.O algorithm that provide the improved result in the stop and pass band. Digital FIR filter has been fabricated in this paper by using Blackman, Flat-top and Kaiser window function. The designed filter i.e. FIR using Kaiser window function provides the improved results. PSO algorithm has been applied on designed filter to further optimize the design in MATLAB. Results obtained by using PSO show that devised F.I.R filter is superior than earlier devised F.I.R filter with reference to frequency spectrum.