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Volume 32 Issue 1
Aug.  2010
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Cao Hong-bing, Wei Jian-ming, Liu Hai-tao. Research on Multi-Sensor Feature Fusion Algorithms in Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2010, 32(1): 166-171. doi: 10.3724/SP.J.1146.2008.01800
Citation: Cao Hong-bing, Wei Jian-ming, Liu Hai-tao. Research on Multi-Sensor Feature Fusion Algorithms in Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2010, 32(1): 166-171. doi: 10.3724/SP.J.1146.2008.01800

Research on Multi-Sensor Feature Fusion Algorithms in Wireless Sensor Networks

doi: 10.3724/SP.J.1146.2008.01800
  • Received Date: 2008-12-26
  • Rev Recd Date: 2009-06-11
  • Publish Date: 2010-01-19
  • A multi-sensor feature fusion algorithm based on improved Local Discriminant Bases (LDB) and Binary Particle Swarm Optimization (BPSO) is proposed in this paper to satisfy the requirement of application on classification of ground targets in wireless sensor networks. LDB is improved by a new discriminant measure using relative differential entropy based on probability density estimation and used to extract the characteristic frequency band of signals. Then an improved and a new BPSO are used for feature fusion respectively. Based on real acoustic and seismic signals of ground targets, experiment results indicate that this method can decrease the classifier number needed, reduce the dimension of features, and improve the performance of classification at a certain extent, so it is practically valuable for application.
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