New stability criterion of neural networks with leakage delays and impulses: a piecewise delay method
| Autor: | G. Sugumaran, Ramachandran Raja, R. Suresh Kumar, Quanxin Zhu, U. Karthik Raja |
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| Rok vydání: | 2015 |
| Předmět: |
Equilibrium point
0209 industrial biotechnology Artificial neural network Stability criterion Cognitive Neuroscience Linear matrix inequality Monotonic function 02 engineering and technology 020901 industrial engineering & automation Exponential stability Control theory 0202 electrical engineering electronic engineering information engineering Piecewise 020201 artificial intelligence & image processing Differentiable function Research Article Mathematics |
| Zdroj: | Cognitive Neurodynamics. 10:85-98 |
| ISSN: | 1871-4099 1871-4080 |
| Popis: | This paper analyzes the global asymptotic stability of a class of neural networks with time delay in the leakage term and time-varying delays under impulsive perturbations. Here the time-varying delays are assumed to be piecewise. In this method, the interval of the variation is divided into two subintervals by its central point. By developing a new Lyapunov–Krasovskii functional and checking its variation in between the two subintervals, respectively, and then we present some sufficient conditions to guarantee the global asymptotic stability of the equilibrium point for the considered neural network. The proposed results which do not require the boundedness, differentiability and monotonicity of the activation functions, can be easily verified via the linear matrix inequality (LMI) control toolbox in MATLAB. Finally, a numerical example and its simulation are given to show the conditions obtained are new and less conservative than some existing ones in the literature. |
| Databáze: | OpenAIRE |
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