On Global Dissipativity of Nonautonomous Neural Networks With Multiple Proportional Delays

IEEE Trans Neural Netw Learn Syst. 2018 Jan;29(1):225-231. doi: 10.1109/TNNLS.2016.2614998. Epub 2016 Oct 19.

Abstract

This brief addresses the problem of global dissipativity analysis of nonautonomous neural networks with multiple proportional delays. By using a novel constructive approach based on some comparison techniques for differential inequalities, new explicit delay-independent conditions are derived using M-matrix theory to ensure the existence of generalized exponential attracting sets and the global dissipativity of the system. The method presented in this brief is also utilized to derive a generalized exponential estimate for a class of Halanay-type inequalities with proportional delays. Finally, three numerical examples are given to illustrate the effectiveness and improvement of the obtained results.