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Updated: Jul 19, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Some new stability properties of dynamic neural networks with different time-scales
Wen Yu1, Alejandro Cruz Sandoval
1Departamento de Control Automatico, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, DF México. yuw@ctrl.cinvestav.mx
Abstract:
Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of these networks to be stable. The main contribution of the paper is that Lyapunov function and singularly perturbed technique are combined to access several new stable properties of different time-scales neural networks. Exponential stability and asymptotic stability are obtained by sector and bound conditions. Compared to other papers, these conditions are simpler. Numerical examples are given to demonstrate the effectiveness of the theoretical results.
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