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Please use this identifier to cite or link to this item:
http://ir.ncue.edu.tw/ir/handle/987654321/11781
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| Title: | Applying the Competitive Hopfield Neural Network to Multiple Target Tracking Systems |
| Authors: | Lin, Y.-J.;Chen, H.-T.;Su, J.-D.;Chen, J.-Y.;Hu, Y.-N.;Chung, Yi-Nung |
| Contributors: | 電機工程學系 |
| Keywords: | Data association;Competitive Hopfield Neural Network |
| Date: | 2005-11
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| Issue Date: | 2012-07-02T02:08:30Z
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| Publisher: | Southern Taiwan University of Technology, Department of Electrical Engineering |
| Abstract: | Data association plays an important role in radar multiple-target tracking algorithm. It will obtain the relations between radar measurements and existing tracks after applying a data association algorithm. A new approach to data association based on the Competitive Hopfield Neural Network (CHNN) is investigated. Moreover, it was also applied to a multiple-target tracking system in order to solve both the data association and the target tracking problems simultaneously. With this approach, the matching between radar measurements and existing target tracks can achieve a global optimal consideration. Computer
simulation results indicate that this approach
successfully and optimally solves the data association
problems. |
| Relation: | 2005 CACS Automatic Control Conference, Tainan, Taiwan, Nov 18-19, 2005 |
| Appears in Collections: | [電機工程學系] 會議論文
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