Abstract / truncated to 115 words (read the full abstract)

This dissertation deals with the distributed processing techniques for parameter estimation and efficient data-gathering in wireless communication and sensor networks. The estimation problem consists in inferring a set of parameters from temporal and spatial noisy observations collected by different nodes that monitor an area or field. The objective is to derive an estimate that is as accurate as the one that would be obtained if each node had access to the information across the entire network. With the aim of enabling an energy aware and low-complexity distributed implementation of the estimation task, several useful optimization techniques that generally yield linear estimators were derived in the literature. Up to now, most of the works considered that ... toggle 12 keywords

adaptive networks – distributed processing – adaptive filtering – cooperation – diffusion – NSPE – node-specific parameter estimation – incremental – LMS – RLS – wireless sensor network – data gathering

Follow @eurasip