Adaptive Filter of Extended Correlation Least Mean Squared Algorithm Based on Tap-Length Variable Method

The conventional algorithms in the echo canceling system have drawback when they are faced with double-talk condition in noisy environment. Since the double-talk and noise signal are exist, then the error signal is contaminated to estimate the gradient correctly. In this paper, we define a new adaptive algorithm for tap adaptations, based on the correlation function processing, which is called Extended Correlation Least Mean Squared (ECLMS) algorithm. And also in this paper, the tap-length variable method is improved into the ECLMS algorithm to reduce the computational complexity. The computer simulation results support the theoretical findings and verify the robustness of the proposed algorithm in the double-talk condition.