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Distributed Detection Using Convolutional Codes

In this thesis, we consider decentralized multiclass classification problem in wireless sensor networks. In literature, the decentralized detection using error correcting code has been shown to have good fault-tolerance capability. In this thesis, we provide fault-tolerance capability by employing the code with a particular structure so that the decoding at the fusion center can be efficient. Specifically, the convolution code is employed to decode the local decision vector sent from all the local sensors. In addition, we proposed an efficient convolution code design algorithm by using simulated annealing. The simulation result shows that the proposed approach has good performance.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0905108-152710
Date05 September 2008
CreatorsWu, Chao-yi
ContributorsChih-Peng Li, Tsang-Yi Wang, Chao-Tang Yu
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905108-152710
Rightsnot_available, Copyright information available at source archive

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