acoustic echo cancellation using LMS algorithm

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acoustic echo cancellation using LMS algorithm

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Acoustic echo cancellation (AEC) is a critical technology in audio communication systems, where echoes caused by sound reflections can degrade call quality. The Least Mean Squares (LMS) algorithm is widely used in AEC due to its simplicity and effectiveness in adaptive filtering.

The MATLAB program developed for this thesis implements the LMS algorithm to cancel acoustic echoes. The core idea involves modeling the echo path with an adaptive filter and continuously adjusting its coefficients to minimize the error between the desired signal and the filtered output. The LMS algorithm achieves this by iteratively updating the filter weights based on the gradient descent method, using the instantaneous error signal to guide adjustments.

Key components of the implementation include: Input Signal Handling: Captures the near-end and far-end signals, where the far-end signal generates the echo. Adaptive Filter: Simulates the echo path and adapts dynamically to changes in the acoustic environment. Error Calculation: Measures the difference between the actual echo and the estimated echo produced by the filter. Coefficient Update: Adjusts filter weights using the LMS rule, balancing convergence speed and stability.

This approach is particularly useful in real-time systems, such as teleconferencing or hands-free communication devices, where low latency and computational efficiency are crucial. The MATLAB implementation serves as a practical demonstration of how LMS-based AEC can enhance audio clarity by effectively suppressing unwanted echoes.