In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
Abstract—To achieve scalability, energy-efficiency, and timeliness, wireless sensor network deployments increasingly employ in-network processing. In this paper, we identify sin...
We propose a distributed implementation of the Gaussian particle filter (GPF) for use in a wireless sensor network. Each sensor runs a local GPF that computes a global state esti...
Ondrej Hlinka, Ondrej Sluciak, Franz Hlawatsch, Pe...
Wireless sensor networks have mainly been designed for information-collecting purposes, such as habitat monitoring, product process tracing, battlefield surveillance, etc. In orde...
Wireless sensor networks provide an attractive approach to spatially monitoring environments. Wireless technology makes these systems relatively flexible, but also places heavy d...