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1. The adaptive algorithm adopts the NLMS (Normalized Least Mean Square) algorithm from reference [2], providing faster convergence speed and reduced training iterations. Implementation typically involves calculating step size normalization using input signal power estimation. 2. Adaptive convergence step size has optimal values within (0, 2) range, with Lorenz sequence analysis determining 0.6 as the optimal parameter through empirical validation.

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