DocumentCode
2133262
Title
Application of subband analysis to adaptive prediction
Author
Saffle, James R. ; Rao, S.S.
Author_Institution
Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA
Volume
3
fYear
1998
fDate
12-15 May 1998
Firstpage
1725
Abstract
A closed-loop adaptive subband prediction architecture is presented by employing an adaptive subband filter in the prediction configuration. Some authors have suggested that applying open-loop prediction methods to subband signals can realize increased prediction gain over fullband prediction. Furthermore, the benefits of applying multirate techniques to adaptive filtering are well understood in terms of reduction of computational complexity and increased convergence speed. Thus, the closed-loop subband adaptive predictor is a novel approach that is expected to exhibit these same benefits along with the advantages of backward adaptation. Results show that the new subband predictor can produce a higher prediction gain than a similar fullband adaptive prediction filter. The proposed architecture is implemented in C++ on the Pentium processor
Keywords
adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; digital filters; filtering theory; least mean squares methods; prediction theory; C++; Pentium processor; adaptive prediction; adaptive subband filter; backward adaptation; closed-loop adaptive subband prediction architecture; computational complexity reduction; convergence speed; fullband prediction; multirate techniques; prediction gain; subband analysis; subband signals; Adaptive filters; Application software; Computational complexity; Computer architecture; Convergence; Delay; Prediction methods; Predictive models; Spectral analysis; Speech coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location
Seattle, WA
ISSN
1520-6149
Print_ISBN
0-7803-4428-6
Type
conf
DOI
10.1109/ICASSP.1998.681791
Filename
681791
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