Abstract
The global exponential stability problem for a class of complex-valued recurrent neural networks with both asynchronous time-varying delays and impulse is concerned in this paper. By using Schur complement and Lyapunov functional, some new sufficient criteria to ascertain globally exponential stability of the equilibrium point are obtained in terms of linear matrix inequality. An example is given to illustrate the effectiveness of the results.
Author supplied keywords
Cite
CITATION STYLE
Zhang, D., Jiang, H., Hu, C., Yu, Z., & Huang, D. (2017). Global Stability of Complex-Valued Neural Networks with Time-Delays and Impulsive Effects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10636 LNCS, pp. 825–835). Springer Verlag. https://doi.org/10.1007/978-3-319-70090-8_84
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
