Global attractivity in delayed Hopfield neural network models
SIAM Journal on Applied Mathematics
On the stability analysis of delayed neural networks systems
Neural Networks
Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Stability analysis of a single neuron model with delay
Journal of Computational and Applied Mathematics
Technical communique: An improved result for complete stability of delayed cellular neural networks
Automatica (Journal of IFAC)
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We investigate the complete stability for multistable delayed neural networks. A new formulation modified from the previous studies on multistable networks is developed to derive componentwise dynamical property. An iteration argument is then constructed to conclude that every solution of the network converges to a single equilibrium as time tends to infinity. The existence of 3n equilibria and 2n positively invariant sets for the n-neuron system remains valid under the new formulation. The theory is demonstrated by a numerical illustration.