Title :
A unified framework for least square and mean square based adaptive filtering algorithms
Author :
Zhang, Zhongkai ; Bose, Tamal ; Gunther, Jacob
Author_Institution :
Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA
Abstract :
This paper presents a unified framework for adaptive filters based on a line search method. Expressions for this unified framework are derived. Based on this framework new algorithms are derived, namely, diagonal Q-correlation matrix least square algorithm (DQLS), block diagonal Q-correlation matrix least square algorithm (BDQLS) and their reduced complexity variants. It is shown that both DQLS and BDQLS have less computational complexity compared to EDS and RLS, and better performance than LMS.
Keywords :
adaptive filters; correlation methods; least mean squares methods; least squares approximations; BDQLS; DQLS; EDS; LMS; RLS; adaptive filtering algorithms; adaptive filters; block diagonal Q-correlation matrix least square algorithm; computational complexity reduction; diagonal Q-correlation matrix least square algorithm; line search method; Adaptive algorithm; Adaptive filters; Computational complexity; Convergence; Filtering algorithms; Jacobian matrices; Least squares approximation; Least squares methods; Resonance light scattering; Search methods;
Conference_Titel :
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN :
0-7803-8834-8
DOI :
10.1109/ISCAS.2005.1465588
