Exponential stability criteria on neural networks with continuously distributed delays

摘要

考虑了一类具有时变和连续分布时滞神经网络系统的指数稳定性问题．通过引入Lyapunov-Krasovskii泛函、自由权矩阵和等价的描述系统形式,针对所考虑的系统建立了一个时滞相关的指数稳定性准则．该准则以线性矩阵不等式的形式给出,能够很容易地用Matlab工具箱LMI进行检验．此外,所得到的结论不需要激励函数的单调性且变时滞的导函数只要有上界结论就可以成立,这拓展和发展了现有的一些结论．最后通过2个数值例子说明了所得结论的有效性．%The exponential stability of a class of neural networks with continuously distributed delays is investigated by employing a novel Lyapunov-Krasovskii functional. Through introducing some free-weighting matrices and the equivalent descriptor form, a delay-dependent stability criterion is established for the addressed systems. The condition is expressed in terms of a linear matrix inequality (LMI), and it can be checked by resorting to the LMI in the Matlab toolbox. In addition, the proposed stability criteria do not require the monotonicity of the activation functions and the derivative of a time-varying delay being less than 1, which generalize and improve earlier methods. Finally, numerical examples are given to show the effectiveness of the obtained methods.