Improved Variable Step Size LMS Algorithm Based on Arctangent Function
2021 China Automation Congress (CAC)(2021)
摘要
The stability and convergence speed of the traditional Least Mean Square (LMS) are always in a state of contradiction due to the fixed step size. According to the relevant researchers, replacing the fixed step size with a time-varying step size, we use the arctangent function to return the transformation of the step-change factor and the error in the Sigmoid Variable step-size LMS (SVSLMS) algorithm. Furthermore, we analyze the influence of the parameters in the step-change factor on the proposed algorithm. The proposed algorithm accelerates convergence speed and solves the problem because the step size changes too quickly of the Normal distribution Sigmoid Variable step-size LMS (N-SVSLMS) algorithm. The simulation conclusion presents the convergence speed of the algorithm is significantly improved.
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关键词
least mean square error,step-change factor,variable step size algorithm,adaptive filtering
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