{"title":"Promoting polynomial predictive filtering on the Internet","authors":"J. Martikainen, S. Ovaska","doi":"10.1109/SECON.2000.845595","DOIUrl":null,"url":null,"abstract":"Polynomial predictive filtering (PPF) is a powerful tool for modern digital signal processing. Still, not as widely known as it should be. To make the new techniques easier to approach, we have established an Internet site, which, at the moment contains illustrative documentation for the recursive linear smoothed Newton (RLSN) and the Heinonen-Neuvo (H-N) finite impulse response (FIR) predictors. Two MATLAB-based easy-to-use filter designers for both the RLSN and the H-N predictors are also available. With the help of these automatic designers, users are offered a convenient way to get to know what polynomial predictive filtering is all about by easily experimenting themselves. The Internet, and the World-Wide Web (WWW) especially, offer a flexible, easily maintainable and popular platform for promoting these ideas and techniques.","PeriodicalId":206022,"journal":{"name":"Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2000.845595","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
Polynomial predictive filtering (PPF) is a powerful tool for modern digital signal processing. Still, not as widely known as it should be. To make the new techniques easier to approach, we have established an Internet site, which, at the moment contains illustrative documentation for the recursive linear smoothed Newton (RLSN) and the Heinonen-Neuvo (H-N) finite impulse response (FIR) predictors. Two MATLAB-based easy-to-use filter designers for both the RLSN and the H-N predictors are also available. With the help of these automatic designers, users are offered a convenient way to get to know what polynomial predictive filtering is all about by easily experimenting themselves. The Internet, and the World-Wide Web (WWW) especially, offer a flexible, easily maintainable and popular platform for promoting these ideas and techniques.