Robust distributed detection over adaptive diffusion networks

Sara Al-Sayed,Abdelhak M. Zoubir,Ali H. Sayed

Acoustics, Speech and Signal Processing（2014）

引用 15|浏览6

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摘要

Diffusion adaptation techniques based on the least-mean-squares criterion have been proposed for distributed detection of a signal in Gaussian-distributed noise, forgoing the need for a fusion center. However, least-mean-squares solutions are generally non-robust against impulsive noise. In this work, we combine nonlinear filtering with diffusion adaptation and propose a strategy for distributed detection in the presence of impulsive noise. The superiority of the algorithm is validated experimentally.

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关键词

impulse noise,least mean squares methods,nonlinear filters,signal detection,Gaussian-distributed noise,adaptive diffusion networks,impulsive noise,least-mean-squares criterion,nonlinear filtering,robust distributed detection,Adaptive networks,diffusion LMS,error nonlinearity,hypothesis testing,robust distributed detection

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