Wu Ailong, Zeng Zhigang
College of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China; School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Institute for Information and System Science, Xi'an Jiaotong University, Xi'an 710049, China.
School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China.
Neural Netw. 2016 Feb;74:73-84. doi: 10.1016/j.neunet.2015.11.003. Epub 2015 Nov 11.
We show that the ω-periodic fractional-order fuzzy neural networks cannot generate non-constant ω-periodic signals. In addition, several sufficient conditions are obtained to ascertain the boundedness and global Mittag-Leffler stability of fractional-order fuzzy neural networks. Furthermore, S-asymptotical ω-periodicity and global asymptotical ω-periodicity of fractional-order fuzzy neural networks is also characterized. The obtained criteria improve and extend the existing related results. To illustrate and compare the theoretical criteria, some numerical examples with simulation results are discussed in detail.
我们证明了ω周期分数阶模糊神经网络不能生成非恒定的ω周期信号。此外，还获得了几个充分条件，以确定分数阶模糊神经网络的有界性和全局Mittag-Leffler稳定性。此外，还刻画了分数阶模糊神经网络的S渐近ω周期性和全局渐近ω周期性。所得到的准则改进并扩展了现有的相关结果。为了说明和比较理论准则，详细讨论了一些带有仿真结果的数值例子。
