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Development of the Hopfield Neural Scheme for Data Association in Multi-target Tracking

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

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Abstract

The neural scheme for data association in multi-target environment is proposed. This scheme is derived by using the Lyapunov energy function and is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. Through the experiments, we show that the proposed scheme is stable and works well in general environments.

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References

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Author information

Authors and Affiliations

  1. Department of Information and Communication Engineering, Honam University, Seobongdong, Gwangsangu, Gwangju, 506-714, South Korea

    Yang Weon Lee

Authors
  1. Yang Weon Lee
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Lee, Y.W. (2006). Development of the Hopfield Neural Scheme for Data Association in Multi-target Tracking. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_190

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  • DOI: https://doi.org/10.1007/11759966_190

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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