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Further Research on Extended Alternating Projection Neural Network

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Advanced Intelligent Computing Theories and Applications (ICIC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6215))

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Abstract

In order to apply the Extended Alternating Projection Neural Network (EAPNN) better in pattern recognition, signal processing and sensor network, the paper makes futher research on the EAPNN and deduces several important conclusions from the mathematical expression to the steady state value of EAPNN, and strict mathematical proofs to these corollaries are also given. In addition, the convergent speed of EAPNN has been discussed and analyzed.

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References

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Author information

Authors and Affiliations

  1. New Star Research Institute of Applied Technology, 451 Huangshan Road, Hefei, Anhui, China

    Jingen Wang, Yanfei Wang & Xunxue Cui

Authors
  1. Jingen Wang
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  2. Yanfei Wang
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  3. Xunxue Cui
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Editor information

Editors and Affiliations

  1. Intelligent Computing Laboratory, Chinese Academy of Sciences, P.O. Box 1130, 230031, Hefei, Anhui, China

    De-Shuang Huang

  2. Department of Biomedical Informatics, Vanderbilt University Medical Center, 2,525 West End Avenue, Suite 600, 37203, Nashville, TN, USA

    Zhongming Zhao

  3. Electrical and Electronics Department, Polytechnic of Bari, Via Orabona 4, 70125, Bari, Italy

    Vitoantonio Bevilacqua

  4. Faculty of Engineering, District University Francisco José de Caldas, Cra. 7a,No. 40-53, Fifth Floor, Bogotá, Colombia

    Juan Carlos Figueroa

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© 2010 Springer-Verlag Berlin Heidelberg

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Wang, J., Wang, Y., Cui, X. (2010). Further Research on Extended Alternating Projection Neural Network. In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-14922-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14921-4

  • Online ISBN: 978-3-642-14922-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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