Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects.
basic_science · Level V
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- Record sourced from PubMed, PMID 24806759.
- Also identified by DOI 10.1109/TNNLS.2012.2192135.
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Abstract
This paper focuses on the hybrid effects of parameter uncertainty, stochastic perturbation, and impulses on global stability of delayed neural networks. By using the Ito formula, Lyapunov function, and Halanay inequality, we established several mean-square stability criteria from which we can estimate the feasible bounds of impulses, provided that parameter uncertainty and stochastic perturbations are well-constrained. Moreover, the present method can also be applied to general differential systems with stochastic perturbation and impulses.
Medical subject headings
- Algorithms
- Models, Statistical
- Neural Networks, Computer
- Nonlinear Dynamics
- Pattern Recognition, Automated
- Stochastic Processes