A global stability analysis of a particular class of recurrent neural networks with time-varying delay is performed. Both Lipschitz continuous and monotone non-decreasing activation functions are considered. Globally asymptotically delay-dependent stability criteria are derived in the form of linear matrix inequalities through the use of Leibniz-Newton formula and relaxation matrices. Finally, two numerical examples are given to illustrate the effectiveness of the given criterion.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Science Applications
- Control and Optimization
- Electrical and Electronic Engineering