Year: 2017
Author: Yajing Wang, Zhenkun Huang
Journal of Mathematical Study, Vol. 50 (2017), Iss. 4 : pp. 323–338
Abstract
In this paper, we investigate global stability of complex-valued periodic solution of a delayed discontinuous neural networks. By employing discontinuous, nondecreasing and bounded properties of activation, we analyzed exponential stability of state trajectory and $L^1$−exponential convergence of output solution for complex-valued delayed networks. Meanwhile, we applied to complex-valued discontinuous neural networks with periodic coefficients. The new results depend on $M$−matrices of real and imaginary parts and hence can include ones of real-valued neural networks. An illustrative example is given to show the effectiveness of our theoretical results.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/jms.v50n4.17.03
Journal of Mathematical Study, Vol. 50 (2017), Iss. 4 : pp. 323–338
Published online: 2017-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 16
Keywords: Complex-valued Periodic solutions Global exponential stability Discontinuous neural networks.