{"title":"Adaptive envelope-constrained filter design","authors":"C. Tseng, K. Teo, A. Cantoni","doi":"10.1109/ISCAS.2000.858694","DOIUrl":null,"url":null,"abstract":"A new type of adaptive scheme was proposed recently for designing a deterministic envelope-constrained (EC) filter such that the generated sequence of filters converges to the optimum filter. Previous results at this level of generality linked convergence only to within a neighborhood of the optimum filter. Based on the adaptive scheme, two new theorems are established in a stochastic environment for which the adaptive EC filter converges in mean square sense and with probability one to the noiseless optimum filter for a fixed step-size and a decreasing sequence of step-sizes, respectively. Numerical examples involving pulse compression Barker-coded signal are studied for solving the EC filtering problem.","PeriodicalId":6422,"journal":{"name":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2000.858694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A new type of adaptive scheme was proposed recently for designing a deterministic envelope-constrained (EC) filter such that the generated sequence of filters converges to the optimum filter. Previous results at this level of generality linked convergence only to within a neighborhood of the optimum filter. Based on the adaptive scheme, two new theorems are established in a stochastic environment for which the adaptive EC filter converges in mean square sense and with probability one to the noiseless optimum filter for a fixed step-size and a decreasing sequence of step-sizes, respectively. Numerical examples involving pulse compression Barker-coded signal are studied for solving the EC filtering problem.
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