Variant of the charged system search algorithm for the design of optimal linear phase finite impulse response filters

R P Meenaakshi Sundhari,S N Deepa

doi:10.1080/00051144.2019.1570632

Abstract

ABSTRACT Digital signal filtering is one of the prime area which is frequently used in practical applications. In the class of digital filters, the prominent filters include – filters with finite impulse response (FIR) and filters with infinite impulse response (IIR). Low pass, high pass, band pass and band stop filters are the different types of filters that are currently employed for carrying out filtering actions. Filters are used for practical applications to reduce the noise incurred while processing the signals received, whether it may be an audio signal, video signal, bio-medical signal and so on. The key features for the design of filters include the optimization of coefficients and in turn the design of coefficients is based on attaining maximum stop band attenuation with less ripple rates. This paper proposes the soft computing based wavelet concept being introduced in the charged system search algorithm at the updation process. The scaling factor in the updation equation is implemented with a wavelet introduced to improve the exploration and exploitation capability of the algorithm. This introduction of wavelet into the algorithm results in faster convergence of the algorithm and proves its effectiveness in comparison with that of the other approaches as available in the literature.

Highlights

In this paper, work is carried out on the design of linear phase optimal finite impulse response (FIR) filter types
The constriction factor based particle swarm optimization (PSO) algorithm produces a set of filter coefficients and tries to satisfy the required ideal frequency characteristic, for the given problem, the realization of the FIR band pass filters of various order has been conducted by Kar et al [5]
A wavelet based operation is carried out for enhancing the scaling factor involved in the updation equation of the basic charged system search algorithm

Summary

Introduction

Work is carried out on the design of linear phase optimal FIR filter types. On analysing the growing evolutionary optimization techniques and carrying out an extensive literature survey, it was observed widely all the evolutionary techniques – genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), bee colony algorithm, gravitational search algorithm (GSA), harmony search algorithm (HSA), Tabu search algorithm, fuzzy adaptive simulated annealing, bacterial foraging optimization algorithm and variants and hybrid approaches of these algorithms – have been actively utilized in order to compute the optimal FIR filter coefficients for all types of filters. The constriction factor based PSO algorithm produces a set of filter coefficients and tries to satisfy the required ideal frequency characteristic, for the given problem, the realization of the FIR band pass filters of various order has been conducted by Kar et al [5]. The newly proposed approach has proven to be better in comparison with the solutions available in the literature

Problem definition

Findings

Summary