Distributed estimation strategies over wireless sensor networks are one of the active areas
of research due to the wide range of applications in a variety of fields ranging from …

In wireless sensor networks (WSNs), distributed algorithms are used to estimate desired
parameters for minimizing the communication overheads and make the network energy …

This paper proposes robust diffusion maximum versoria criterion algorithms to enhance the
performance of the distributed estimation in a network of agents under impulsive noise …

We consider distributed recursive estimation of an unknown vector parameter in the
presence of impulsive communication noise. That is, we assume that interagent …

The classical distributed sparse regression based on least square error is sensitive to the
outliers in the desired data. In this manuscript, we consider the rank based estimator named …

Least squared error cost function based conventional diffusion strategies are not robust
against outliers in both the desired and input data. In most of the practical scenarios, both …

In the present world, distributed signal processing plays a significant role in applications
ranging from surveillance and tracking to exploration and monitoring. In this paper, an online …

The least squares based affine projection algorithm (APA) is sensitive to outliers/impulsive
noise in the desired data. A novel robust APA over distributed networks scenario is …

We consider distributed recursive estimation of consensus+ innovations type in the
presence of heavy-tailed sensing and communication noises. We allow that the sensing and …

This work develops a robust diffusion recursive least squares algorithm to mitigate the
performance degradation often experienced in networks of agents in the presence of …