{"title":"Word-length optimization of LMS adaptive FIR filters","authors":"M. Leban, J. Tasic","doi":"10.1109/MELCON.2000.880048","DOIUrl":null,"url":null,"abstract":"The paper deals with the word-length optimization of LMS adaptive FIR filters using fixed-point arithmetic. As the optimization criterion, a weighted sum of the mean-square error /spl xi/, area and delay of the adaptive filter considering target implementation technology is used. Because the optimization is performed by a computer and there is no need to have a simple expression for manual reviewing, a more accurate expression for the mean-square error has been derived considering an improved quantization model. Word-length optimization was performed by a genetic algorithm because classical optimization methods were not suitable for such optimization. Simulation results are given for an adaptive echo canceller.","PeriodicalId":151424,"journal":{"name":"2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries. Proceedings. MeleCon 2000 (Cat. No.00CH37099)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries. Proceedings. MeleCon 2000 (Cat. No.00CH37099)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MELCON.2000.880048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Word-length optimization of LMS adaptive FIR filters
The paper deals with the word-length optimization of LMS adaptive FIR filters using fixed-point arithmetic. As the optimization criterion, a weighted sum of the mean-square error /spl xi/, area and delay of the adaptive filter considering target implementation technology is used. Because the optimization is performed by a computer and there is no need to have a simple expression for manual reviewing, a more accurate expression for the mean-square error has been derived considering an improved quantization model. Word-length optimization was performed by a genetic algorithm because classical optimization methods were not suitable for such optimization. Simulation results are given for an adaptive echo canceller.