Boundedness and stability for discrete-time delayed neural network with complex-valued linear threshold neurons
Summary: Discrete-time delayed neural network with complex-valued linear threshold neurons is considered. By constructing appropriate Lyapunov-Krasovskii functionals and employing a linear matrix inequality technique and analysis method, several new delay-dependent criteria for checking the boundedness and global exponential stability are established. Illustrating examples are also given to show the effectiveness and less conservatism of the proposed criteria.
scientific article; zbMATH DE number 5793488