Hu Cheng, Jiang Haijun, Teng Zhidong
the College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China.
IEEE Trans Neural Netw. 2010 Jan;21(1):67-81. doi: 10.1109/TNN.2009.2034318. Epub 2009 Nov 20.
This paper discuss the global exponential stability and synchronization of the delayed reaction-diffusion neural networks with Dirichlet boundary conditions under the impulsive control in terms of p-norm and point out the fact that there is no constant equilibrium point other than the origin for the reaction-diffusion neural networks with Dirichlet boundary conditions. Some new and useful conditions dependent on the diffusion coefficients are obtained to guarantee the global exponential stability and synchronization of the addressed neural networks under the impulsive controllers we assumed. Finally, some numerical examples are given to demonstrate the effectiveness of the proposed control methods.
本文从p范数的角度讨论了具有Dirichlet边界条件的时滞反应扩散神经网络在脉冲控制下的全局指数稳定性和同步性,并指出具有Dirichlet边界条件的反应扩散神经网络除原点外不存在常数平衡点。得到了一些依赖于扩散系数的新的有用条件,以保证在我们假设的脉冲控制器下所研究神经网络的全局指数稳定性和同步性。最后,给出了一些数值例子来证明所提出控制方法的有效性。