DocumentCode
2622072
Title
An intelligent LMS+F algorithm
Author
Pazaitis, Dimitrios I. ; Constantinides, A.G.
Author_Institution
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
fYear
1996
fDate
24-26 Jun 1996
Firstpage
486
Lastpage
489
Abstract
A new technique for combining the LMS and LMF cost functions is proposed. The resulting stochastic gradient adaptive algorithm uses a time varying mixing parameter to optimise a combination of the above cost functions, taking into consideration the noise statistics. Furthermore, the behaviour of the proposed algorithm is analysed and convergence conditions are established. Simulation results verify the ability of the algorithm to adapt itself to the noise characteristics, illustrate its enhanced performance and support very well the theoretic analysis. The continuous adaptation of the mixing parameter adds flexibility and enables rapid response of the algorithm to non-stationarities
Keywords
adaptive signal processing; convergence of numerical methods; least mean squares methods; noise; parameter estimation; statistical analysis; stochastic processes; LMF cost functions; LMS; convergence; intelligent LMS+F algorithm; mixing parameter; noise characteristics; noise statistics; nonstationarities response; performance; simulation results; stochastic gradient adaptive algorithm; time varying mixing parameter; Adaptive algorithm; Adaptive signal processing; Algorithm design and analysis; Convergence; Cost function; Educational institutions; Least squares approximation; Scholarships; Signal processing algorithms; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004
Conference_Location
Corfu
Print_ISBN
0-8186-7576-4
Type
conf
DOI
10.1109/SSAP.1996.534920
Filename
534920
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