{"title":"Structural design of microwave photonic filter based on adaptive genetic algorithm with disturbance operation","authors":"Xiangnong Wu, Ye Yin, J. Zhang, Qiang Ni","doi":"10.1109/PGC.2012.6458093","DOIUrl":null,"url":null,"abstract":"In this paper, the optimization for an FBG array based microwave photonic filter using adaptive genetic algorithm with disturbance operation is proposed, established and studied. In the design we assume that the population size is 50, the maximum number of iterations is 50, the FBG reflectivity is from 0 to 1 and there are six uniform FBGs in the FBG array. The simulation results show that the optimized simulation time can be reduced by half, from 23.5 seconds to 10.8 seconds, compared with that using the traditional genetic algorithm without disturbance. The influences of the number of the FBGs and the range of the tap coefficients of the FBGs are detailed studied. The amplitude frequency response of the MPF will deteriorate when the range of the tap coefficients of the FBGs become smaller. The simulation results for different values of stopband rejections show that the proposed algorithm is feasible.","PeriodicalId":158783,"journal":{"name":"2012 Photonics Global Conference (PGC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Photonics Global Conference (PGC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PGC.2012.6458093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the optimization for an FBG array based microwave photonic filter using adaptive genetic algorithm with disturbance operation is proposed, established and studied. In the design we assume that the population size is 50, the maximum number of iterations is 50, the FBG reflectivity is from 0 to 1 and there are six uniform FBGs in the FBG array. The simulation results show that the optimized simulation time can be reduced by half, from 23.5 seconds to 10.8 seconds, compared with that using the traditional genetic algorithm without disturbance. The influences of the number of the FBGs and the range of the tap coefficients of the FBGs are detailed studied. The amplitude frequency response of the MPF will deteriorate when the range of the tap coefficients of the FBGs become smaller. The simulation results for different values of stopband rejections show that the proposed algorithm is feasible.