Article thumbnail
Location of Repository

Controlling chaos in a chaotic neural network

By Dr G. He, Prof. Z. Cao, Prof. P. Zhu and Prof. H. Ogura


The chaotic neural network constructed with chaotic neuron shows the associative memory function, but its memory searching process cannot be stabilized in a stored state because of the chaotic motion of the network. In this paper, a pinning control method focused on the chaotic neural network is proposed. The computer simulation proves that the chaos in the chaotic neural network can be controlled with this method and the states of the network can converge in one of its stored patterns if the control strength and the pinning density are chosen suitable. It is found that in general the threshold of the control strength of a controlled network is smaller at higher pinned density and the chaos of the chaotic neural network can be controlled more easily if the pinning control is added to the variant neurons between the initial pattern and the target pattern

Topics: Dynamical Systems, Neural Nets, Artificial Intelligence
Publisher: Elsevier Science Ltd.
Year: 2003
DOI identifier: 10.1016/s0893-6080(03)00055-8
OAI identifier:

Suggested articles


  1. (1997). Associative dynamics in a chaotic neural network.
  2. (1987). Chaos in biological systems.
  3. (1990). Chaotic neural networks.
  4. (1995). Controlling a simple chaotic neural network using response to perturbation.
  5. (1995). Controlling chaos in neural networks.
  6. (1990). Controlling chaos.
  7. (1994). Controlling spatiotemporal chaos in coupled map lattice systems.
  8. (1996). Model of dynamic associative memory.
  9. (1987). Simulation of chaotic EEG patterns with a dynamic model of the olfactory system.
  10. (1991). Stabling high-period orbits in a chaotic system: the diode resonator.

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.