DocumentCode :
2099618
Title :
Adaptive Filter by Using Segment Proportionate Extended Correlation LMS Algorithm in the Double-Talk Condition
Author :
Chen, Rui ; E, Zhifeng ; Hu, Jiawen ; Asharif, Mohammad Reza
Author_Institution :
Comput. Sci. Coll., CSUFT Changsha, Changsha, China
Volume :
2
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
716
Lastpage :
719
Abstract :
Echo path estimation in echo canceling for teleconference system is a problem in double-talk condition. The correlation-processing algorithms were defined by the authors to solve this problem. In this paper, we proposed a new promotional algorithm with fast convergence speed - proportionate extended correlation LMS algorithm (PECLMS). The idea of the PECLMS algorithm is introducing an improved proportionate adaptation into the ECLMS algorithm. Furthermore, we improved the PECLMS algorithm with segment proportionate adaptation. The segment proportionate extended correlation LMS algorithm (SPECLMS) have faster and more stable convergence speed than the PECLMS algorithm. The computer simulation results support the theoretical findings and verify the robustness of the proposed SPECLMS algorithm in the double-talk situation.
Keywords :
adaptive filters; echo suppression; least mean squares methods; LMS algorithm; adaptive digital filtering; double-talk condition; echo canceling; echo path estimation; segment proportionate extended correlation; teleconference system; Adaptive filters; Computer science; Computer simulation; Convergence; Echo cancellers; Filtering algorithms; Finite impulse response filter; Least squares approximation; Microphones; Teleconferencing; Adaptive digital filtering; Correlation function; Double-talk; Echo canceling; LMS algorithm; Segment proportionate adaptation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
Type :
conf
DOI :
10.1109/ISCSCT.2008.265
Filename :
4731723
Link To Document :
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