S. Saha, Annesha Chaudhuri, D. Mandal, R. Kar, S. Ghoshal
{"title":"Optimization of IIR high pass filter using craziness based particle swarm optimization technique","authors":"S. Saha, Annesha Chaudhuri, D. Mandal, R. Kar, S. Ghoshal","doi":"10.1109/SHUSER.2012.6268873","DOIUrl":null,"url":null,"abstract":"In this paper, a variant of particle swarm optimization (PSO), called craziness based particle swarm optimization (CRPSO) is used for the design of 8th order infinite impulse response (IIR) digital filter. The proposed optimization technique is a global heuristic search algorithm and better exploration and exploitation of multidimensional search space can be achieved with closely mimicked swarm behaviour in fundamental PSO equation. Performance of the proposed optimization technique is compared with some well accepted evolutionary algorithms such as PSO and real coded genetic algorithm (RGA). From the simulation study it is established that the CRPSO outperforms RGA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality, i.e., the stop band attenuation, transition width, pass band and stop band ripples. Further, the pole-zero analysis justifies the stability of the designed optimized IIR filter.","PeriodicalId":426671,"journal":{"name":"2012 IEEE Symposium on Humanities, Science and Engineering Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Symposium on Humanities, Science and Engineering Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SHUSER.2012.6268873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, a variant of particle swarm optimization (PSO), called craziness based particle swarm optimization (CRPSO) is used for the design of 8th order infinite impulse response (IIR) digital filter. The proposed optimization technique is a global heuristic search algorithm and better exploration and exploitation of multidimensional search space can be achieved with closely mimicked swarm behaviour in fundamental PSO equation. Performance of the proposed optimization technique is compared with some well accepted evolutionary algorithms such as PSO and real coded genetic algorithm (RGA). From the simulation study it is established that the CRPSO outperforms RGA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality, i.e., the stop band attenuation, transition width, pass band and stop band ripples. Further, the pole-zero analysis justifies the stability of the designed optimized IIR filter.