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

Tanay Dutta, Raina Modak Aich, Supriya Dhabal, P. Venkateswaran
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引用次数: 3

Abstract

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.
基于Grasshopper优化算法的有限脉冲响应滤波器设计及FPGA实现
本文利用蚱蜢优化算法(Grasshopper Optimization Algorithm, GOA)建立了一种高效的1型FIR滤波器设计风格,并在FPGA上实现。GOA是一种基于群体的元启发式优化算法,它是由蝗虫的群体活动驱动的。GOA以其更好的解决问题的能力彻底改变了当代。元启发式优化算法的主要特点是使数字滤波器的最优响应和估计响应中的故障最小化。因此,该算法求解问题集的效率高,在各个领域得到了广泛的认可。此外,为了强调所提出算法的实用性,将模拟结果与Parks McClellan (PM)算法和正弦余弦算法(SCA)等成熟算法的结果进行了比较,发现Grasshopper优化算法(GOA)在阻带衰减和通带纹波方面优于PM和SCA。此外,本文还解释了FPGA平台中正在考虑的概念的硬件功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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