Global Exponential Synchronization of Delayed Fuzzy Neural Networks With Reaction Diffusions
Yin Sheng, Yun Xing, Tingwen Huang, Zhigang Zeng
Abstract
This article is concerned with global exponential synchronization of delayed fuzzy neural networks with reaction diffusions (RDFNNs). By adopting analytic method and some inequality techniques, a global exponential synchronization criterion in terms of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$p$</tex-math></inline-formula> -norm ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$p\geq 2$</tex-math></inline-formula> ) is obtained for the RDFNNs via adaptive intermittent control. One numerical example is provided to demonstrate the validity of the proposed outcomes. Two other examples are given to show the applications in image encryption and pseudorandom number generation, respectively.