| Citation: | Yuanlian HUO, Xiaoqiang LONG, Peijun LIAN, Danfeng WANG. A Kind of Versoria Function Normalized Adaptive Filtering Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(2): 335-340. doi: 10.11999/JEIT191003
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On the basis of the comprehensive consideration in the design of the indexs of the adaptive filter algorithm convergence speed, steady-state error, computational complexity and tracking performance, a kind of Versoria function normalized adaptive filtering algorithm is proposed in this paper. The class Versoria function is used instead of Sigmoid function as step iterative formula, introducing variable step size based on the relevant error adjustment principle, the stability of the algorithm is enhanced greatly. At the same time, the convergence speed and tracking performance of the algorithm is promoted and the computational complexity of the algorithm is reduced. The influence of the parameter
,
and
different value of the step function of algorithm is analyzed on Matlab platform. Compared with the Sigmoid function variable step size LMS algorithm and variable step size LMS algorithm based on Versoria function, and the simulation results show that this algorithm has faster convergence speed, better tracking ability, smaller steady-state error and strong robustness.
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