DocumentCode :
2047793
Title :
Promoting polynomial predictive filtering on the Internet
Author :
Martikainen, Jarno ; Ovaska, Seppo J.
Author_Institution :
Inst. of Intelligent Power Electron., Helsinki Univ. of Technol., Espoo, Finland
fYear :
2000
fDate :
2000
Firstpage :
373
Lastpage :
378
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
Keywords :
FIR filters; IIR filters; Newton method; computer aided instruction; electronic engineering education; information resources; polynomials; prediction theory; recursive filters; smoothing methods; FIR; H-N predictor; Heinonen-Neuvo finite impulse response predictor; Internet site; MATLAB-based easy-to-use filter designer; RLSN; WWW; World-Wide Web; digital signal processing; polynomial predictive filtering; recursive linear smoothed Newton predictor; Computer languages; Digital filters; Digital signal processing; Documentation; Finite impulse response filter; Information filtering; Information filters; Internet; Polynomials; World Wide Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon 2000. Proceedings of the IEEE
Conference_Location :
Nasville, TN
Print_ISBN :
0-7803-6312-4
Type :
conf
DOI :
10.1109/SECON.2000.845595
Filename :
845595
Link To Document :
بازگشت