Robust Variable Step-Size Diffusion Sign-Error Algorithm Over Adaptive Networks
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Although the diffusion sign-error (DSE-LMS) algorithm is robust against impulsive noise, it has a slow convergence rate due to the application of the sign operation. Therefore, this study proposes a robust variable step-size DSE-LMS algorithm to solve the conflict between fast convergence rate and low misadjustment in impulsive noise environments. The step size is obtained by minimizing the l1-norm of the noiseless intermediate posterior error at each node, resulting in improved tracking capability of the proposed algorithm. Furthermore, the mean-square performance is analyzed based on the principle of energy conservation. The simulation results demonstrate that the proposed algorithm distinctly outperforms the existing algorithms in terms of both steady-state error and convergence rate in impulsive noise environments.
KeywordsDiffusion strategy Sign-error algorithm Impulsive noise
This work was supported by the Fund for the National Nature Science Foundation of China (Grant: 61671392).
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