Distributed Learning in Wireless Sensor Networks

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