Fixed-/preassigned-time synchronization for delayed complex-valued neural networks with discontinuous activations.

Cogn Neurodyn

School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, 232001 Anhui People's Republic of China.

Published: October 2024

Finite-time synchronization is a crucial phenomenon observed in nonlinear complex systems, the settling time in such a dynamic phenomenon is heavily depends on the initial states which may be unaccessible beforehand in the real world. Eliminating the dependence of the settling time on initial states leads to major advantage and convenience in practical applications. This paper is concerned with the fixed-/preassigned-time synchronization of delayed complex-valued neural networks(CVNNs) with discontinuous activations. By designing novel state feedback controllers, and with the help of Filippov regularization and inequality techniques, some new criteria for achieving fixed-/preassigned-time synchronization are established. The obtained theoretical results cover and supplement existing ones of the CVNNs with continuous activations. In addition, the upper-bound of the settling time is explicitly estimated. Finally, the validity of the theoretical results is supported by numerical simulations.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564493PMC
http://dx.doi.org/10.1007/s11571-024-10129-6DOI Listing

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