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Synchronization control of memristor-based recurrent neural networks with perturbations
Ist Teil von
Neural networks, 2014-05, Vol.53, p.8-14
Ort / Verlag
Kidlington: Elsevier Ltd
Erscheinungsjahr
2014
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
In this paper, the synchronization control of memristor-based recurrent neural networks with impulsive perturbations or boundary perturbations is studied. We find that the memristive connection weights have a certain relationship with the stability of the system. Some criteria are obtained to guarantee that memristive neural networks have strong noise tolerance capability. Two kinds of controllers are designed so that the memristive neural networks with perturbations can converge to the equilibrium points, which evoke human’s memory patterns. The analysis in this paper employs the differential inclusions theory and the Lyapunov functional method. Numerical examples are given to show the effectiveness of our results.