Modified artificial bee colony optimisation based FIR filter design with experimental validation using field-programmable gate array

Atul Kumar Dwivedi, Subhojit Ghosh, N. Londhe
{"title":"Modified artificial bee colony optimisation based FIR filter design with experimental validation using field-programmable gate array","authors":"Atul Kumar Dwivedi, Subhojit Ghosh, N. Londhe","doi":"10.1049/iet-spr.2015.0214","DOIUrl":null,"url":null,"abstract":"Optimisation based design of finite impulse response (FIR) filters has been an active area of research for quite some time. The various algorithms proposed for FIR filter design aim at meeting a set of desired specifications in the frequency domain. Evolutionary algorithms have been found to be very effective for FIR filter design because of the non-linear, non-differentiable and non-convex nature of the associated optimisation problem. The present work proposes two modified versions of a recently developed evolutionary technique i.e. artificial bee colony (ABC) algorithm for design of FIR filters. The applicability of the proposed approach has been evaluated by comparing its response with conventional reported filter design techniques. The proposed variants of ABC are found to outperform other non-convex algorithms in achieving the desired specifications. In addition to the simulation results, the designed filters have been implemented in hardware using Xilinx-xc7vx330t-3ffg1157 (Virtex-7) field programmable gate array. The hardware implementation allows validation of the proposed techniques for practical filtering applications by considering real time operation parameters.","PeriodicalId":272888,"journal":{"name":"IET Signal Process.","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Signal Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/iet-spr.2015.0214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

Abstract

Optimisation based design of finite impulse response (FIR) filters has been an active area of research for quite some time. The various algorithms proposed for FIR filter design aim at meeting a set of desired specifications in the frequency domain. Evolutionary algorithms have been found to be very effective for FIR filter design because of the non-linear, non-differentiable and non-convex nature of the associated optimisation problem. The present work proposes two modified versions of a recently developed evolutionary technique i.e. artificial bee colony (ABC) algorithm for design of FIR filters. The applicability of the proposed approach has been evaluated by comparing its response with conventional reported filter design techniques. The proposed variants of ABC are found to outperform other non-convex algorithms in achieving the desired specifications. In addition to the simulation results, the designed filters have been implemented in hardware using Xilinx-xc7vx330t-3ffg1157 (Virtex-7) field programmable gate array. The hardware implementation allows validation of the proposed techniques for practical filtering applications by considering real time operation parameters.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于现场可编程门阵列的改进人工蜂群优化FIR滤波器设计与实验验证
基于优化设计的有限脉冲响应(FIR)滤波器一直是一个活跃的研究领域相当长一段时间。FIR滤波器设计的各种算法都是为了在频域满足一组期望的规范。进化算法已被发现是非常有效的FIR滤波器设计,因为相关的优化问题的非线性,不可微和非凸性质。本工作提出了两个改进版本的最新发展的进化技术,即人工蜂群(ABC)算法的设计FIR滤波器。通过将其响应与传统报道的滤波器设计技术进行比较,评估了所提出方法的适用性。在实现期望的规范方面,发现ABC的拟议变体优于其他非凸算法。除了仿真结果外,所设计的滤波器已使用Xilinx-xc7vx330t-3ffg1157 (Virtex-7)现场可编程门阵列在硬件上实现。硬件实现允许通过考虑实时操作参数来验证所提出的技术在实际过滤应用中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An order insensitive optimal generalised sequential fusion estimation for stochastic uncertain multi-sensor systems with correlated noise Spatial Multiplexing in Near Field MIMO Channels with Reconfigurable Intelligent Surfaces An improved segmentation technique for multilevel thresholding of crop image using cuckoo search algorithm based on recursive minimum cross entropy Advances in image processing using machine learning techniques An unsupervised monocular image depth prediction algorithm using Fourier domain analysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1