Hyper-Exponential Stabilization of Neural Networks by Event-Triggered Impulsive Control With Actuation Delay.
IEEE Trans Neural Netw Learn Syst
; PP2024 Jun 06.
Article
in En
| MEDLINE
| ID: mdl-38843063
ABSTRACT
This brief studies the hyper-exponential stabilization of neural networks (NNs) by event-triggered impulsive control, where the impulse instants are determined by the event-triggered conditions. In the presence of actuation delay, an event-triggered impulsive control scheme is devised. For reducing the sampling task of continuous detection, a periodic-detection scheme is also introduced. Within these frameworks, the occurrence of Zeno behavior is rigorously precluded, and some criteria are formulated to achieve the stabilization of the system with a hyper-exponential convergence rate. Moreover, a numerical simulation is provided to elucidate the validity of the theoretical findings.
Full text:
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Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
IEEE Trans Neural Netw Learn Syst
Year:
2024
Document type:
Article