Skip to main content
SpringerLink
Log in

From Hopfield Nets to Pulsed Neural Networks

  • Conference paper
Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4234))

Included in the following conference series:

  • 2217 Accesses

Abstract

Considering the first two generations of Artificial Neural Networks, Hopfield model is the only active system. Studying this type of network, a relation between this artificial neural network and the third generation, characterized by spiking neurons, was noticed. This paper presents the relationship between the Hopfield Neural Networks and the Pulsed Neural Networks. This relation is shown by the integration of the Hopfield neuron model, ending in an integrate-and-fire model, with the appropriate choice of the input kernels.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gerstner, W.: Time structure of the activity in neural networks models. Phys. Riview 51, 738–748 (1995)

    Article  Google Scholar 

  2. Usher, M., Schuster, H.G., Niebur, E.: Dynamics of populations of integrate and fire neurons. Neural Computation 5, 570–586 (1993)

    Article  Google Scholar 

  3. Rieke, F., Warland, D., de Ruyter van Steveninck, R., Bialek, W.: Spikes: Exploring the Neural Coding. MIT Press, Cambridge (1996)

    Google Scholar 

  4. Maass, W., Bishop, C.M.: Pulsed Neural Networks. MIT Press, England (2001)

    Google Scholar 

  5. Haykin, S.: Neural Network: A comprehensive foundation. Prentice Hall, New Jersey (1999)

    MATH  Google Scholar 

  6. Guerreiro, A.M.G.: A New Paradigm for Neurocomputation Using the Boolean Complete Neuron, Ph.D Thesis, University of Colorado (May 2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Rio Grande do Norte Federal University, Natal RN, Brazil

    Ana M. G. Guerreiro

  2. University of Colorado, Colorado Springs, CO, USA

    Carlos A. Paz de Araujo

Authors
  1. Ana M. G. Guerreiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carlos A. Paz de Araujo
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

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

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Guerreiro, A.M.G., de Araujo, C.A.P. (2006). From Hopfield Nets to Pulsed Neural Networks. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_128

Download citation

  • DOI: https://doi.org/10.1007/11893295_128

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46484-6

  • Online ISBN: 978-3-540-46485-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation