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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
Summary
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.
- Confirmed findings through analysis and simulation.
Conclusions:
- Binary attractor neural networks exhibit SSR.
- External stimuli can reveal SSR in these networks.
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