Liu Xiaoyang, Park Ju H, Jiang Nan, Cao Jinde
Nonlinear Dynamics Group, Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan 712-749, Republic of Korea; School of Computer Science & Technology, Jiangsu Normal University, Xuzhou 221116, China.
Nonlinear Dynamics Group, Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan 712-749, Republic of Korea.
Neural Netw. 2014 Apr;52:25-32. doi: 10.1016/j.neunet.2014.01.004. Epub 2014 Jan 11.
This paper is concerned with the finite-time stabilization for a class of neural networks (NNs) with discontinuous activations. The purpose of the addressed problem is to design a discontinuous controller to stabilize the states of such neural networks in finite time. Unlike the previous works, such stabilization objective will be realized for neural networks when the activations and controllers are both discontinuous. Based on the famous finite-time stability theorem of nonlinear systems and nonsmooth analysis in mathematics, sufficient conditions are established to ensure the finite-time stability of the dynamics of NNs. Then, the upper bound of the settling time for stabilization can be estimated in two forms due to two different methods of proof. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design method.
本文关注一类具有不连续激活函数的神经网络(NNs)的有限时间镇定问题。所研究问题的目的是设计一个不连续控制器,以便在有限时间内镇定此类神经网络的状态。与先前的工作不同,当激活函数和控制器均为不连续时,将针对神经网络实现这种镇定目标。基于著名的非线性系统有限时间稳定性定理以及数学中的非光滑分析,建立了充分条件以确保神经网络动力学的有限时间稳定性。然后,由于两种不同的证明方法,可以以两种形式估计镇定的调节时间上限。最后,给出两个数值例子来说明所提出设计方法的有效性。