Stability and Synchronization Control of Stochastic Neural Networks by Wuneng Zhou Jun Yang Liuwei Zhou & Dongbing Tong

Author:Wuneng Zhou, Jun Yang, Liuwei Zhou & Dongbing Tong
Language: eng
Format: epub
Publisher: Springer Berlin Heidelberg, Berlin, Heidelberg

In this example, the activation function is assumed to satisfy (H) with .

Then, by the Matlab LMI toolbox, the maximum allowed delay satisfying the LMI in (5.6) can be calculated as and the system is stable for any .

By choosing , system (5.6) with is asymptotically stable, as shown in Fig. 5.1.

Fig. 5.1The solution trajectory of Example 5.11

Example 5.12

Consider the delayed neural network in (5.5) with the following parameters:

Let , and by applying Theorem 5.8, there exists a feasible solution which guarantees the robust stability of the system (5.5):

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