Synchronization of Generally Uncertain Markovian Inertial Neural Networks With Random Connection Weight Strengths and Image Encryption Application

This article focuses on the synchronization problem of delayed inertial neural networks (INNs) with generally uncertain Markovian jumping and their applications in image encryption. The random connection weight strengths and generally uncertain Markovian are discussed in the INNs model. Compared wit...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2023-09, Vol.34 (9), p.5911-5925
Main Authors: Wang, Junyi, Ji, Zewen, Zhang, Huaguang, Wang, Zhanshan, Meng, Qinggang
Format: Article
Language:English
Subjects:
Biological neural networks
Delay-product-term Lyapunov–Krasovskii functional (DPTLKF)
higher order polynomial based relaxed inequality (HOPRII)
Human factors
inertial neural networks (INNs)
Linear matrix inequalities
Mathematical analysis
Neural networks
Neurons
Polynomials
random connection weight strengths
Stability analysis
Symmetric matrices
Synchronism
Synchronization
Transmission line measurements
Weight
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Summary:This article focuses on the synchronization problem of delayed inertial neural networks (INNs) with generally uncertain Markovian jumping and their applications in image encryption. The random connection weight strengths and generally uncertain Markovian are discussed in the INNs model. Compared with most existing INNs models that have constant connection weight strengths, our model is more practical because connection weight strengths of INNs may randomly vary due to the external and internal environment and human factor. The delay-range-dependent synchronization conditions (DRDSCs) could be obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII). In addition, the desired controllers are obtained by solving a set of linear matrix inequalities. Finally, two examples are shown to demonstrate the effectiveness of the proposed results.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2021.3131512