Abstract
The popular distributed estimation algorithms based on the mean-square error criterion is not robust against impulsive noise in the adaptive networks. To address the problem, the diffusion least logarithmic absolute difference (LLAD) algorithm is proposed in this article, which adopts both the logarithm operation and sign operation to the error. The algorithm can elegantly and gradually adjust the conventional cost functions in its optimization based on the error variation. Compared with centralized LLAD algorithm, the diffusion LLAD algorithm performs a good balance between communications and performance. The theoretical stability of mean and mean-square performance of the algorithm is analyzed. Simulation results indicate that the algorithm achieves a better performance, compared with diffusion LMS and diffusion sign-error LMS algorithms, even in the impulsive noise environment.
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