计算机科学
协议(科学)
同步(交流)
跳跃
马尔可夫链
扩散
分布式计算
并行计算
计算机网络
医学
物理
频道(广播)
替代医学
病理
量子力学
机器学习
热力学
作者
Wenhai Qi,Zhenzhen Yuan,Guangdeng Zong,Jinde Cao,Huaicheng Yan,Jun Cheng,Shan Jin
标识
DOI:10.1109/tcyb.2024.3502684
摘要
This study investigates the synchronization of reaction-diffusion complex dynamical networks (CDNs) based on semi-Markov switching topology and an event-triggered protocol. The investigated model is rendered more practical via the introduction of a semi-Markov process for stochastic jump CDNs. Based on the internal dynamic variable history information, a dynamic-memory event-triggered strategy is proposed, wherein the primary novelty lies in its prior transmitted packets to enhance the control performance. This further reduces data transmission based on the dynamic threshold parameters. The Bessel-Legendre inequality is adopted to reduce the conservatism of the obtained results. In addition, sufficient synchronization conditions are established to ensure the stochastic stability of the error system for two different models (partial differential equations-and ordinary differential equations-based models). Furthermore, two examples are provided to illustrate the effectiveness of the theoretical results.
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