Distributed parameter estimation in unreliable sensor networks via broadcast gossip algorithms. (January 2016)

• Record Type: Journal Article
• Authors: Wang, Huiwei; Liao, Xiaofeng; Wang, Zidong; Huang, Tingwen; Chen, Guo
• Is Part Of: Neural networks. Volume 73(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-01
• Subjects: Broadcast gossip algorithm -- Distributed parameter estimation -- Quantized communication -- Unreliable sensor networks; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2015.09.008
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: In this paper, we present an asynchronous algorithm to estimate the unknown parameter under an unreliable network which allows new sensors to join and old sensors to leave, and can tolerate link failures. Each sensor has access to partially informative measurements when it is awakened. In addition, the proposed algorithm can avoid the interference among messages and effectively reduce the accumulated measurement and quantization errors. Based on the theory of stochastic approximation, we prove that our proposed algorithm almost surely converges to the unknown parameter. Finally, we present a numerical example to assess the performance and the communication cost of the algorithm.