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Artificial neural networks

Dissipativity Analysis and Bumpless Transfer Control for Synchronization of Switched Delayed Neural Networks: A New Approach

Strategic Insights

— 1 min read

Researchers from Northeastern University have made a breakthrough in the field of networks by developing a new method for dissipativity analysis and bumpless transfer control for synchronization of switched delayed neural networks (SDNNs). The study, funded by the National Natural Science Foundation of China, China Postdoctoral Science Foundation, and Open Project Program of Center for Applied Mathematics of Fujian Province, Fuzhou University, has been peer-reviewed and published in the Ieee Transactions On Systems Man Cybernetics-systems.

The research team, led by Jun Fu, has proposed a modified combined switching approach that offers a less conservative framework for the dissipativity analysis of SDNNs. The approach involves constructing a new time-dependent multiple Lyapunov-Krasovskii functional (TDMLF) to ensure the strict (X-1,X-2,X-3)-gamma dissipativity for the considered SDNNs. The proposed method is implemented for the synchronization of SDNNs, where a bumpless transfer proportional-integral-like (PI-like) control approach is first adopted.

Key Takeaways:

  • The researchers have developed a new method for dissipativity analysis and bumpless transfer control for synchronization of SDNNs.
  • The proposed approach offers a less conservative framework for the dissipativity analysis of SDNNs.
  • The method involves constructing a new time-dependent multiple Lyapunov-Krasovskii functional (TDMLF) to ensure the strict (X-1,X-2,X-3)-gamma dissipativity for the considered SDNNs.
  • The proposed approach is implemented for the synchronization of SDNNs, where a bumpless transfer proportional-integral-like (PI-like) control approach is first adopted.
  • The researchers have demonstrated the practicability and superiority of the proposed design approach through two simulation examples.

Statistics:

  • The research was funded by the National Natural Science Foundation of China, China Postdoctoral Science Foundation, and Open Project Program of Center for Applied Mathematics of Fujian Province, Fuzhou University.
  • The study was peer-reviewed and published in the Ieee Transactions On Systems Man Cybernetics-systems.
  • The research team consisted of Jun Fu, Hong Sang, Fang Li, Shuaibing Zhu, and Hong Nie from Northeastern University.
  • The proposed approach has been demonstrated to offer a less conservative framework for the dissipativity analysis of SDNNs.

Sources:

  • Ieee Transactions On Systems Man Cybernetics-systems, "Dissipativity Analysis and Bumpless Transfer Control for Synchronization of Switched Delayed Neural Networks: a Modified Combined Switching Approach," 2025; 55(10): 6913-6924.
  • NewsRx, "Study Findings from Northeastern University Provide New Insights into Networks (Dissipativity Analysis and Bumpless Transfer Control for Synchronization of Switched Delayed Neural Networks: a Modified Combined Switching Approach)," Journal of Engineering, October 20, 2025, p 4323.

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