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Diffusion sign-error LMS algorithm: Formulation and stochastic behavior analysis

机译:扩散符号错误LMS算法:公式化和随机行为分析

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摘要

In the case where the measurement noise involves impulsive interference, distributed estimation algorithms based on the mean-square error (MSE) criterion may suffer from severely degraded convergence performance or divergence. To address this problem, we modify the adapt-then-combine (ATC) diffusion LMS (DLMS) algorithm by applying the sign operation to the error signals at all agents to develop a diffusion sign-error LMS (DSE-LMS) algorithm. Furthermore, the stochastic behavior of the DSE-LMS algorithm is analyzed for Gaussian inputs and contaminated Gaussian noise based on Price's theorem. Simulation results show the robustness of the DSE-LMS algorithm against impulsive interference and validate the theoretical findings.
机译:在测量噪声涉及脉冲干扰的情况下,基于均方误差(MSE)准则的分布式估计算法可能会严重降低收敛性能或发散性。为了解决此问题,我们通过对所有代理处的错误信号应用符号运算来修改自适应联合组合(ATC)扩散LMS(DLMS)算法,以开发扩散符号错误LMS(DSE-LMS)算法。此外,基于Price定理,分析了DSE-LMS算法针对高斯输入和受污染的高斯噪声的随机行为。仿真结果表明了DSE-LMS算法抗脉冲干扰的鲁棒性,并验证了理论结果。

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