Finite Impulse Response Filter Design using Grasshopper Optimization Algorithm and Implementation on FPGA

This paper establishes an efficient design style of Type-1 FIR filter using Grasshopper Optimization Algorithm (GOA) and its implementation on FPGA. GOA is a newly developed population-based meta-heuristic optimization algorithm motivated by the swarming activities of grasshoppers. GOA with its better problem-solving capability has revolutionized the contemporary era. Minimization of faults in the optimum response and the estimated response in digital filters are the main feature of meta-heuristic optimization algorithms. Therefore, this algorithm has been broadly accepted in various fields due to its high efficiency in solving problem sets. Further, to emphasis the usefulness of the suggested algorithm, the simulated outcomes have been compared with the results of the well-established algorithms such as Parks McClellan (PM) Algorithm and Sine Cosine Algorithm (SCA) and it has been found that Grasshopper Optimization Algorithm (GOA) outperform PM and SCA in terms of stop-band attenuation and pass-band ripple. Additionally, this paper also explains the hardware function of the concept being contemplated within the FPGA platform.