A novel approach for optimal design of digital FIR filter using grasshopper optimization algorithm

The idea behind designing digital filters is to compute the optimal filter coefficients such that the magnitude response of the designed matches the ideal frequency response using optimization algorithms. The proposed work employed a recently proposed swarm-based optimization technique, namely, a grasshopper optimization algorithm (GOA) to design a linear phase finite impulse response (FIR) low pass, high pass, band pass , and band stop filters. This proposed algorithm models the behaviour of grasshoppers while seeking food sources to solve optimization problems. For the designing of the FIR filter, an absolute error difference fitness function is used, which is minimized using GOA to obtain optimal filter coefficients. The performance comparison of the proposed work is done with already existing algorithms such as cuckoo search, particle swarm optimization, artificial bee colony to prove its superiority and consistency. It is found that GOA based filter meets the objective efficiently with reduced ripples in pass band and higher attenuation in stop band with least execution time. (c) 2020 ISA. Published by Elsevier Ltd. All rights reserved.

Automated summary

The study utilized a grasshopper optimization algorithm to design digital filters and compute optimal filter coefficients to achieve the desired objectives. An absolute error difference fitness function was used for the design of the FIR filter, minimizing errors for optimal coefficients. Performance comparison with existing algorithms showed the superiority of the proposed GOA-based filter design.