Designing an M-Order Adaptive Echo Canceller

Design an M-order adaptive echo canceller using u(n) as system input and d(n) as desired system response, where d(n) contains echoes of u(n). With signals sampled at 8kHz, the echo canceller must eliminate echoes within 16ms. Implementation requires careful selection of adaptive filtering algorithms and proper parameter configuration to handle the specified echo path delay.

Several Common Adaptive Filtering Algorithms in Echo Cancellers

This article discusses several adaptive filtering algorithms commonly used in echo cancellers, including LMS, NLMS, and RLS algorithms. The performance of these algorithms is analyzed, and their advantages and disadvantages are evaluated and compared. To achieve a better trade-off between convergence speed and computational complexity, the NLMS algorithm is improved, resulting in the PNLMS algorithm with enhanced implementation characteristics for real-time applications.

Adaptive Filtering in Echo Cancellers

Simulation of Adaptive Filtering in Echo Cancellers using MATLAB with Code Implementation Details

Speech Signal Separation Using NLMS Algorithm

This program employs the NLMS (Normalized Least Mean Squares) algorithm to separate dual-channel speech signals, utilizing an echo canceller mathematical model with enhanced processed speech output, demonstrating significant performance improvements.