文章基本信息

标题：Comparative Evaluation of FIR Filter Design with Genetic Algorithm and Particle Swarm Optimization
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作者：Anita Suman ; Parveen Kumar ; Asha Rani 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：5
页码：2362-2367
出版社：Shri Pannalal Research Institute of Technolgy
摘要：The paper presents a viable methodology for designing linear phase digital FIR filter using particle swarm optimization and genetic algorithm. Evolutionary approach is a better choice than classical gradient based approaches as these are not efficient enough for accurate design. In this paper comparative analysis of FIR filter has been done using genetic algorithm and particle swarm optimization and it is found that results using PSO are better than genetic algorithm. FIR filter design involves multi parameter and multi-modular optimization. We can use different optimization techniques to determine the impulse response coefficient of a filter to meet the characteristics of ideal frequency response. Comparison of simulation results depicts the optimization effectiveness of the particle swarm optimization algorithm over the genetic algorithm optimization techniques for solving non-differentiable, multi modal, highly non-linear, and constrained FIR filter design problems. Now a days, digital signal processing is the vital part of the human life, due to its various applications like telecommunication, consumer electronics systems, biomedical systems, speech processing, image processing, military and defense electronics systems, aerospace and automotive electronics systems. Digital filters can be applied to very low frequency signals occurring in like biomedical and seismic applications very efficiently
关键词：FIR Filter; GA; gbest; lbest; PSO; pbest