Robust distributed detection over adaptive diffusion networks

Autor: Sara Al-Sayed, Abdelhak M. Zoubir, Ali H. Sayed
Předmět:
Zdroj: ICASSP
Popis: 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.
Databáze: OpenAIRE