Title :
Fast tracking two stage adaptive noise canceller
Author :
Al-Saleh, Mohammed A.
Author_Institution :
Comput. Eng. Dept., Umm Al-Qura University, Makkah
Abstract :
This paper presents a Fast Tracking Two Stage Adaptive Noise Canceller (FTTSANC) technique that increases the capability of fast tracking in nonstationary environments of the TSANCA (Two Stage Adaptive Noise Canceller algorithm), especially when more sudden changes in the noise level occur after the settlement of convergence of the TSANC algorithm. The tractability of conventional ANC (Adaptive Noise Canceller) using the LMS (Least Mean Square) algorithm is improved at any time invariant. FTTSANC algorithm can be used to decrease both the convergence times of the LMS and the steady state error making it more effective than the LMS algorithm at tracking in nonstationary environments
Keywords :
interference suppression; least mean squares methods; speech recognition; tracking; FTTSANC technique; LMS; convergence time; fast tracking two stage adaptive noise canceller; least mean square; steady state error; Adaptive filters; Change detection algorithms; Convergence; Least squares approximation; Noise cancellation; Noise level; Speech recognition; Steady-state; Switches; Transversal filters;
Conference_Titel :
TENCON 2004. 2004 IEEE Region 10 Conference
Conference_Location :
Chiang Mai
Print_ISBN :
0-7803-8560-8
DOI :
10.1109/TENCON.2004.1414493
