Title :
Partial update EDS algorithms for adaptive filtering
Author :
Xie, Bei ; Bose, Tamal
Author_Institution :
Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Abstract :
In practice, computational complexity is an important consideration of an adaptive signal processing system. A well-known approach to controlling computational complexity is applying partial update (PU) adaptive filters. In this paper, a partial update Euclidean Direction Search (EDS) algorithm is employed. The theoretical analyses of mean and mean-square performance are presented. The simulation results of different PU EDS are shown.
Keywords :
adaptive filters; adaptive signal processing; computational complexity; mean square error methods; Euclidean direction search algorithm; adaptive filtering; adaptive signal processing system; computational complexity; mean-square performance; partial update EDS algorithms; Adaptive filters; Adaptive signal processing; Computational complexity; Computational efficiency; Computational modeling; Convergence; Filtering algorithms; Performance analysis; Resonance light scattering; Signal processing algorithms; EDS; partial updates;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5495857
