{"title":"最小相位声波滤波器自适应相位均衡的遗传算法","authors":"V. Hegde, S. Pai, W. Jenkins, T. B. Wilborn","doi":"10.1109/ACSSC.2000.911269","DOIUrl":null,"url":null,"abstract":"This paper investigates the capability of the genetic algorithm to achieve convergence to the global minimum for a multi-section all-pass IIR adaptive filter used for digital receiver phase equalization. The effect of population size and mutation rate on the performance of the algorithm is considered. Adaptive crossover and mutation probabilities are used to improve the performance of the algorithm.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"252 1","pages":"1649-1652 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Genetic algorithms for adaptive phase equalization of minimum phase SAW filters\",\"authors\":\"V. Hegde, S. Pai, W. Jenkins, T. B. Wilborn\",\"doi\":\"10.1109/ACSSC.2000.911269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the capability of the genetic algorithm to achieve convergence to the global minimum for a multi-section all-pass IIR adaptive filter used for digital receiver phase equalization. The effect of population size and mutation rate on the performance of the algorithm is considered. Adaptive crossover and mutation probabilities are used to improve the performance of the algorithm.\",\"PeriodicalId\":10581,\"journal\":{\"name\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"volume\":\"252 1\",\"pages\":\"1649-1652 vol.2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2000.911269\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2000.911269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic algorithms for adaptive phase equalization of minimum phase SAW filters
This paper investigates the capability of the genetic algorithm to achieve convergence to the global minimum for a multi-section all-pass IIR adaptive filter used for digital receiver phase equalization. The effect of population size and mutation rate on the performance of the algorithm is considered. Adaptive crossover and mutation probabilities are used to improve the performance of the algorithm.