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Exponential stability for stochastic neural networks of neutral type with impulsive effects. (English) Zbl 1195.82066
Investigated are those dynamical models of stochastic neural networks of neutral type with impulse effects, for which the activation function and diffusion coefficient satisfy some specific boundedness conditions and in addition the diffusion coefficient is locally Lipschitz continuous. In case a set of linear matrix inequalities are satisfied, one proves that the equilibrium point of the system is globally exponentially stable. A classical Lyapunov functional method is used. The sufficient conditions are tested on a two-neuron neural network.
82C32Neural nets (statistical mechanics)