Finite-time stability of fractional-order delayed Cohen–Grossberg memristive neural networks: a novel fractional-order delayed Gronwall inequality approach
Feifei Du, Jun‐Guo Lu · International Journal of General Systems · 2021
This article is dedicated to the improved approach for the finite-time stability (FTS) of fractional-order delayed Cohen–Grossberg memristive neural networks (FDCGMNNs). First, a novel delayed integer-order Gronwall inequality is established. Second, on the basis of this inequality, a novel fractional-order delayed Gronwall inequality is developed. Third, a novel FTS criterion of FDCGMNNs is derived by virtue of the novelly developed fractional-order delayed Gronwall inequality. Eventually, the effectiveness and less conservativeness of the proposed results are shown by two numerical examples.