Global Exponential Stability of Multitime Scale Competitive Neural Networks With Nonsmooth Functions

@article{Lu2006GlobalES,
  title={Global Exponential Stability of Multitime Scale Competitive Neural Networks With Nonsmooth Functions},
  author={Hongtao Lu and Shun-ichi Amari},
  journal={IEEE Transactions on Neural Networks},
  year={2006},
  volume={17},
  pages={1152-1164}
}
In this paper, we study the global exponential stability of a multitime scale competitive neural network model with nonsmooth functions, which models a literally inhibited neural network with unsupervised Hebbian learning. The network has two types of state variables, one corresponds to the fast neural activity and another to the slow unsupervised modification of connection weights. Based on the nonsmooth analysis techniques, we prove the existence and uniqueness of equilibrium for the system… CONTINUE READING