A New Looped Functional to Synchronize Neural Networks With Sampled-Data Control.
basic_science · Level V
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- Record sourced from PubMed, PMID 33055041.
- Also identified by DOI 10.1109/TNNLS.2020.3027862.
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Abstract
This article deals with the problem of sampled-data-based synchronization of neural networks with and without considering time delay. A novel looped functional is introduced in the construction of Lyapunov functional, which adequately utilizes the state information of e(t<sub>k</sub>) , e(t) , e(t<sub>k+1</sub>) , e(t<sub>k</sub>-τ<sub>c</sub>) , e(t-τ<sub>c</sub>) , and e(t<sub>k+1</sub>-τ<sub>c</sub>) . Then, by using this functional and employing a generalized free-matrix-based integral inequality (GFMBII), several sufficient conditions are derived to ensure that the slave system is synchronous with the master system. Also, the sampled-data controller can be obtained by using the linear matrix inequality (LMI) technique. Finally, two numerical examples are illustrated to show the validity and advantages of the proposed method.