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The Algorithms of Distributed Learning and Distributed Estimation about Intelligent Wireless Sensor Network

机译:智能无线传感器网络的分布式学习和分布式估计算法

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摘要

The intelligent wireless sensor network is a distributed network system with high “network awareness”. Each intelligent node (agent) is connected by the topology within the neighborhood which not only can perceive the surrounding environment, but can adjusts its own behavior according to its local perception information to constructs a distributed learning algorithms. Therefore, three basic intelligent network topologies of centralized, non-cooperative, and cooperative are intensively investigated in this paper. The main contributions of the paper include two aspects. First, based on algebraic graph, three basic theoretical frameworks for distributed learning and distributed parameter estimation of cooperative strategy are surveyed: increment strategy, consensus strategy, and diffusion strategy. Second, based on classical adaptive learning algorithm and online updating law, the implementation process of distributed estimation algorithm and the latest research progress of above three distributed strategies are investigated.
机译:智能无线传感器网络是具有高度“网络意识”的分布式网络系统。每个智能节点(代理)都通过邻近区域内的拓扑结构进行连接,不仅可以感知周围的环境,而且可以根据其本地感知信息调整自己的行为,从而构建分布式学习算法。因此,本文深入研究了集中式,非协作式和协作式三种基本的智能网络拓扑。本文的主要贡献包括两个方面。首先,基于代数图,研究了协作策略的分布式学习和分布式参数估计的三个基本理论框架:增量策略,共识策略和扩散策略。其次,基于经典自适应学习算法和在线更新规律,研究了分布式估计算法的实现过程以及上述三种分布式策略的最新研究进展。

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