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.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0905108-152710 |
| Date | 05 September 2008 |
| Creators | Wu, Chao-yi |
| Contributors | Chih-Peng Li, Tsang-Yi Wang, Chao-Tang Yu |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905108-152710 |
| Rights | not_available, Copyright information available at source archive |
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