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.