LMS Adaptive Equalization Simulation
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Resource Overview
Detailed Documentation
The LMS adaptive equalization simulation program implements a multi-tap filtering algorithm that performs signal equalization under specified signal-to-noise ratio (SNR) conditions. The program processes input signals through multiple filter taps and adaptively adjusts filter coefficients based on SNR conditions to achieve optimal signal equalization. The implementation typically involves calculating the error signal between the desired and actual outputs, updating tap weights using the LMS algorithm's gradient descent approach, and applying these weights to the multi-tap filter structure for real-time signal correction. Key functions include SNR-based step size adaptation and tap weight vector updates to minimize mean square error while maintaining convergence stability.
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