A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of WSNs

Neurocomputing

Volumn 117, Issue , 2013, Pages 72-80

  Li, Shuai ^a   Qin, Feng ^b  

^a Stevens Institute of Technology   (United States)

^b ANHUI UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Distributed estimation; Range free localization; Recurrent neural network; Routing free localization; Wireless sensor networks

Indexed keywords

ANALOG CIRCUIT IMPLEMENTATION; DISTRIBUTED ESTIMATION; DYNAMIC NEURAL NETWORKS; NEURAL NETWORK FEATURES; RANGE-FREE LOCALIZATIONS; REAL-TIME COMPUTATIONS; ROUTING-FREE LOCALIZATION; WIRELESS SENSOR NETWORK (WSNS);

PARALLEL ARCHITECTURES; RECURRENT NEURAL NETWORKS; TOPOLOGY;

WIRELESS SENSOR NETWORKS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLINICAL EFFECTIVENESS; COMPUTER PROGRAM; FEASIBILITY STUDY; INTERMETHOD COMPARISON; MACHINE LEARNING; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT; PROCESS MODEL; WIRELESS SENSOR NETWORK;

EID: 84878952647     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.01.032     Document Type: Article

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