… , consensus and diffusion strategies for distributed estimation where diffusion strategy is
reported to have more advantages [1]. Diffusion-based algorithms for distributed estimation are …

… Motivated by the recent works on robust sparse distribution algorithms, in this brief, our aim
is to design a proportionate diffusion LMS algorithm which is robust to impulsive noise. The …

… distributed estimation problems where a set of agents are used for jointly estimating an …
By using the adaptation-then-combination rule in the traditional diffusion least mean square (…

… Then, we analyze the stability and convergence of the D-ABC-LMS algorithm, and …
estimates, we propose a diffusion mixed average-estimate bias-compensated LMS (D-MABC-LMS) …

… study the distributed estimation problem under attacks, which is mainly used to estimate an
unknown parameter. To solve this problem, a correction-based secure diffusion least mean …

… distributed estimation algorithm is devised. We modify the doubly compressed diffusion LMS
(… on one bit distributed estimation [37], robust distributed estimation against impulsive noise […

… strategies in the stochastic setting due to gradient noise [26], [27]. By using constant step-sizes,
diffusion strategies … performance analysis of diffusion LMS strategy in the presence of …

… distributed estimation problem with colored noise over adaptive networks. The nodes estimate
… thus leads to a bias in the diffusion least squares algorithm. Accordingly, we propose a …

… the implications of fading and path loss in diffusion LMS, our study delves into the non-ideal
channel effects on the partial diffusion LMS strategy. To the best of our understanding, the …

… Champagne, “Diffusion lms algorithms for sensor networks … International Conference on
Distributed Computing in Sensor … , “Diffusion lms strategies for parameter estimation over fading …