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System-size resonance in a binary attractor neural network.

M A de la Casa1, E Korutcheva, J M R Parrondo

  • 1Departamento Física Fundamental, Universidad Nacional de Educación a Distancia, c/Senda del Rey 9, 28080 Madrid, Spain. macasa@fisfun.uned.es

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 26, 2005
PubMed
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System size resonance (SSR) was observed in binary attractor neural networks. The network

Area of Science:

  • Computational neuroscience
  • Complex systems

Background:

  • System size resonance (SSR) describes optimal system response at a specific finite size.
  • Binary attractor neural networks are models of associative memory.

Purpose of the Study:

  • To investigate SSR phenomena in binary attractor neural networks.
  • To analyze network response to external stimuli.

Main Methods:

  • Analytical calculations.
  • Computer simulations.
  • Studied network in the ferromagnetic phase.

Main Results:

  • Demonstrated SSR in binary attractor neural networks.
  • Observed signal amplification dependent on network size.

Related Experiment Videos

  • Confirmed findings through analysis and simulation.

    • Conclusions:

    • Binary attractor neural networks exhibit SSR.
    • External stimuli can reveal SSR in these networks.