Distributed Learning in Wireless Sensor Networks

Details Distributed Learning in Wireless Sensor Networks Distributed Learning in Wireless Sensor Networks

2005-03-26

arxiv.org/abs/cs/0503072v1

Computer Science

Information Theory

Published in the Proceedings of the 42nd Annual Allerton Conference on Communication, Control and Computing, University of Ill

Scientific paper

The problem of distributed or decentralized detection and estimation in applications such as wireless sensor networks has often been considered in the framework of parametric models, in which strong assumptions are made about a statistical description of nature. In certain applications, such assumptions are warranted and systems designed from these models show promise. However, in other scenarios, prior knowledge is at best vague and translating such knowledge into a statistical model is undesirable. Applications such as these pave the way for a nonparametric study of distributed detection and estimation. In this paper, we review recent work of the authors in which some elementary models for distributed learning are considered. These models are in the spirit of classical work in nonparametric statistics and are applicable to wireless sensor networks.

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