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Log-domain implementation of complex dynamics reaction-diffusion neural networks.

T Serrano-Gotarredona1, B Linares-Barranco

  • 1Centro Nacional de Microelectron., Inst. de Microelectron. de Sevilla, Spain.

IEEE Transactions on Neural Networks
|February 5, 2008
PubMed
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Researchers developed a novel hardware implementing a reaction-diffusion equation to simulate complex spatio-temporal behaviors. This system successfully reproduced traveling waves, trigger waves, and isolated oscillatory cells, demonstrating its capability for complex dynamics.

Area of Science:

  • Complex Systems
  • Nonlinear Dynamics
  • Hardware Implementation

Background:

  • Reaction-diffusion equations are fundamental models for complex spatio-temporal phenomena.
  • Previous hardware implementations faced limitations in dynamic range and parameter adjustability.

Purpose of the Study:

  • To develop and validate a novel log-domain hardware for simulating second-order reaction-diffusion equations.
  • To demonstrate the hardware's capability in reproducing complex spatio-temporal behaviors.

Main Methods:

  • Identified a second-order reaction-diffusion differential equation capable of diverse spatio-temporal behaviors.
  • Designed a log-domain hardware implementing the spatially discretized equation using MOS transistors.
  • Implemented equation parameters as adjustable currents for wide dynamic range.

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Main Results:

  • The log-domain hardware achieved several decades of variation in state variables and parameters.
  • A chip with ten coupled cells successfully reproduced traveling waves and trigger waves.
  • Isolated oscillatory cell behavior was also experimentally demonstrated.

Conclusions:

  • The developed log-domain hardware effectively simulates complex spatio-temporal dynamics governed by reaction-diffusion equations.
  • This approach offers a versatile platform for studying nonlinear phenomena with a wide dynamic range.