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Global robust stability for stochastic interval neural networks with continuously distributed delays of neutral type. (English) Zbl 1196.34107

Consider stochastic interval neural networks with distributed delays of neutral type equation:

$\begin{array}{c}d\left[x\left(t\right)-Dx\left(t-\mu \left(t\right)\right)\right]=\hfill \\ \left[-Ax\left(t\right)+{W}^{\left(1\right)}f\left(x\left(t\right)\right)+{W}^{\left(2\right)}f\left(x\left(t-\tau \left(t\right)\right)\right)+{W}^{\left(3\right)}{\int }_{-\infty }^{t}K\left(t-s\right)f\left(x\left(s\right)\right)ds\right]dt\\ \hfill +\sigma \left(t,x\left(t\right),x\left(t-\tau \left(t\right)\right),x\left(t-\mu \left(t\right)\right)\right)d\omega \left(t\right)·\end{array}$

The author studies stochastic stability for interval neural networks with continuously distributed delays of neutral type. Using a Lyapunov-Krasovskii functional and LMI technique, the author obtains sufficient conditions for global robust stability. Obtained results are demonstrated by using the MATLAB LMI control toolbox.

##### MSC:
 34K50 Stochastic functional-differential equations 34K20 Stability theory of functional-differential equations 34K40 Neutral functional-differential equations 92B20 General theory of neural networks (mathematical biology)
Matlab
##### References:
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