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Memory Retrieval in a Neural Network with Chaotic Neurons and Dynamic Synapses

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Book cover Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

An associative neural network with chaotic neuron model and synaptic depression (CSDNN) is constructed. Memory switching phenomenon in the network is demonstrated. Simulation results show that with various parameter value settings and with various initial conditions, the memory retrieval frequency of CSDNN distributes uniformly among the stored patterns, and the rate of memory retrieval of CSDNN is much higher than that of a chaotic neural network. The possible utilization of memory retrieval in CSDNN is also discussed.

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Author information

Authors and Affiliations

  1. College of Information Science and Technology, Donghua University, 200051, Shanghai, China

    Zhijie Wang

  2. Glorious sun School of Business and Management, Donghua University, 200051, Shanghai, China

    Hong Fan

Authors
  1. Zhijie Wang
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  2. Hong Fan
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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, Z., Fan, H. (2005). Memory Retrieval in a Neural Network with Chaotic Neurons and Dynamic Synapses. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_80

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  • DOI: https://doi.org/10.1007/11494669_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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