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August 13, 2026
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Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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Enhancing synchronization criteria for fractional-order chaotic neural networks via intermittent control: an extended dissipativity approach

MATHEMATICAL MODELLING AND CONTROL. 2025. Vol. 5. No. 1. P. 31–47.
Shanmugam S., Srinivasan S., Vadivel R., Hammachukiattikul P., Gunasekaran N.

In this paper, a recurrent intermittent control (RIC) for the synchronization of fractional-order chaotic neural networks (FOCNNs) is proposed in view of the extended dissipativity-based approach. Successively, standard linear matrix inequalites (LMIs)-based extended dissipative criteria are derived through differential inclusions and inequality mechanisms. Several sufficient conditions are obtained to ensure the synchronization of FOCNNs. Furthermore, RIC is generated to solve the synchronization problem for the considered FOCNNs. Based on the piecewise Lyapunov functional, this paper derives a exponentially stable criterion in connection with linear matrix inequalities using the Matlab toolbox. Extended dissipativity can be employed to precisely define L2–L∞, H∞, passivity, and (Q, S, R)-ϑ dissipative performance. This is achieved by modifying the weighting matrices to achieve the desired performance level. The successful application of the stability criterion that was planned is demonstrated by the outcomes of the simulation.

Research target: Natural Sciences Mathematics Computer Science Physics
Language: English
DOI
Text on another site
Keywords: chaosFractional calculusComplex System Analysiscyber attacks
Publication based on the results of:
Complex language and semantic models in artificial intelligence (2025)
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