This article studies the H exponential synchronization problem for complex networks with quantized control input. An aperiodic sampled-data-based event-triggered scheme is introduced to reduce the network workload. Based on the discrete-time Lyapunov theorem, a new method is adopted to solve the sampled-data problem. In view of the aforementioned method, several sufficient conditions to ensure the H exponential synchronization are acquired. Numerical simulations show that the proposed control schemes can significantly reduce the amount of transmitted signals while preserving the desired system performance.
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http://dx.doi.org/10.1109/TCYB.2021.3052098 | DOI Listing |
Sci Rep
January 2025
Heilongjiang Ground Pressure and Gas Control in Deep Mining Key Laboratory, Heilongjiang University of Science and Technology, Harbin, 15002, China.
When underground tunnels in coal mines traverse geological structurally abnormal zones (faults, collapse columns, fractured zones, etc.), excavation-induced unloading leads to instability and failure of the engineering rock mass. Rock masses in fractured zones are in elastic, plastic, and post-peak stress states, and the process of excavation through these zones essentially involves unloading under full stress paths.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
Center for Research, SRM Institute of Science and Technology-Ramapuram, Chennai, India.
In this study, we investigate the impact of first and second-order coupling strengths on the stability of a synchronization manifold in a Discrete FitzHugh-Nagumo (DFHN) neuron model with memristor coupling. Master Stability Function (MSF) is used to estimate the stability of the synchronized manifold. The MSF of the DFHN model exhibits two zero crossings as we vary the coupling strengths, which is categorized as class .
View Article and Find Full Text PDFFront Comput Neurosci
December 2024
Institute of Software Engineering and Theoretical Computer Science, Technische Universitaet Berlin, Berlin, Germany.
We adapt non-linear optimal control theory (OCT) to control oscillations and network synchrony and apply it to models of neural population dynamics. OCT is a mathematical framework to compute an efficient stimulation for dynamical systems. In its standard formulation, it requires a well-defined reference trajectory as target state.
View Article and Find Full Text PDFNeural Netw
December 2024
Department of Mathematics Zhejiang Normal University, Zhejiang, 321004, China. Electronic address:
This paper presents cutting-edge advancements in exponential synchronization and encryption techniques, focusing on Quaternion-Valued Artificial Neural Networks (QVANNs) that incorporate two-sided coefficients. The study introduces a novel approach that harnesses the Cayley-Dickson representation method to simplify the complex equations inherent in QVANNs, thereby enhancing computational efficiency by exploiting complex number properties. The study employs the Lyapunov theorem to craft a resilient control system, showcasing its exponential synchronization by skillfully regulating the Lyapunov function and its derivatives.
View Article and Find Full Text PDFISA Trans
December 2024
College of Mathematics and System Science, Xinjiang University, Urumqi 830017, China. Electronic address:
This paper considers the local exponential synchronization problem for a type of complex dynamical networks (CDNs) with both system delay and coupled delay using saturated delayed impulsive control. Based on the methods of average impulsive interval (AII), average impulsive delay (AID) and average impulsive estimation (AIE), a Razumikhin-type inequality with hybrid delayed impulses (which include delayed impulses and delay-free impulses) is derived. This inequality includes pure delayed impulsive inequalities.
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