Abstract
The wavelet transforms are integrated with transform domain LMS adaptive algorithm and variable step-size LMS adaptive algorithm, from which a new adaptive filtering algorithm is presented based on discrete wavelet transforms. The algorithm can reduce the self-correlation of input signals effectively and can overcome the conflict between high convergence rate and low steady state misadjustment in LMS algorithm which leads by fixed step-size. The simulation results indicate that the new algorithm has higher convergence rate and lower misadjustment noise than the traditional LMS algorithm; it can be applied effectively in the adaptive systems.
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