中国物理B ›› 2026, Vol. 35 ›› Issue (3): 30501-030501.doi: 10.1088/1674-1056/adfef7

• • 上一篇    

Statistical complexity and stochastic resonance in bistable coupled network systems excited by non-Gaussian noise

Meijuan He(何美娟)1,3,†, Lingyun Li(李凌云)1,3, Wantao Jia(贾万涛)2, and Jiangang Zhang(张建刚)1,3   

  1. 1 School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China;
    2 School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710129, China;
    3 Gansu Center for Fundamental Research in Complex Systems Analysis and Control, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 收稿日期:2025-05-26 修回日期:2025-08-17 接受日期:2025-08-26 发布日期:2026-02-11
  • 基金资助:
    He Meijuan’s research was partially supported by the Key Project of the Gansu Natural Science Foundation (Grant Nos. 24JRRA226 and 23JRRA882), Lanzhou Youth Science and Technology Talent Innovation Project (Grant No. 2024-QN-179), the Foundation for Innovative Fundamental Research Group Project of Gansu Province, China (Grant No. 25JRRA805), the National Natural Science Foundation of China (Grant Nos. 11602184 and 62463016), the Industrial Support and Guidance Project of Colleges and Universities of Gansu Province (Grant No. 2024CYZC-23), and Tianyou Youth Talent Lift Program of Lanzhou Jiaotong University.

Statistical complexity and stochastic resonance in bistable coupled network systems excited by non-Gaussian noise

Meijuan He(何美娟)1,3,†, Lingyun Li(李凌云)1,3, Wantao Jia(贾万涛)2, and Jiangang Zhang(张建刚)1,3   

  1. 1 School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China;
    2 School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710129, China;
    3 Gansu Center for Fundamental Research in Complex Systems Analysis and Control, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2025-05-26 Revised:2025-08-17 Accepted:2025-08-26 Published:2026-02-11
  • Contact: Meijuan He E-mail:hemeijuan@mail.lzjtu.cn
  • Supported by:
    He Meijuan’s research was partially supported by the Key Project of the Gansu Natural Science Foundation (Grant Nos. 24JRRA226 and 23JRRA882), Lanzhou Youth Science and Technology Talent Innovation Project (Grant No. 2024-QN-179), the Foundation for Innovative Fundamental Research Group Project of Gansu Province, China (Grant No. 25JRRA805), the National Natural Science Foundation of China (Grant Nos. 11602184 and 62463016), the Industrial Support and Guidance Project of Colleges and Universities of Gansu Province (Grant No. 2024CYZC-23), and Tianyou Youth Talent Lift Program of Lanzhou Jiaotong University.

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摘要： This study investigates stochastic resonance (SR) phenomena in bistable coupled networks driven by non-Gaussian noise. Employing signal-to-noise ratio (SNR) and statistical complexity as quantitative metrics, we characterize the SR behavior. First, the dimensionality of a coupled network system is reduced via the mean field theory. Subsequently, we derive closed-form analytical expressions of SNR by the path integral method, the slaving principle and the two-state model theory. Numerical simulations are used to validate the consistency between SR features identified through statistical complexity and those obtained via SNR calculations, thereby corroborating the reliability of our analytical framework. Both theoretical and numerical results conclusively demonstrate the occurrence of SR in the network system. Parametric analyses further elucidate the modulation of SR characteristics by three critical factors: non-Gaussian noise intensity parameters, noise correlation timescale and inter-node coupling strength. Finally, we explore the system’s size resonance properties.

关键词: non-Gaussian noise, bistable coupled network systems, statistical complexity measure, stochastic resonance

Abstract: This study investigates stochastic resonance (SR) phenomena in bistable coupled networks driven by non-Gaussian noise. Employing signal-to-noise ratio (SNR) and statistical complexity as quantitative metrics, we characterize the SR behavior. First, the dimensionality of a coupled network system is reduced via the mean field theory. Subsequently, we derive closed-form analytical expressions of SNR by the path integral method, the slaving principle and the two-state model theory. Numerical simulations are used to validate the consistency between SR features identified through statistical complexity and those obtained via SNR calculations, thereby corroborating the reliability of our analytical framework. Both theoretical and numerical results conclusively demonstrate the occurrence of SR in the network system. Parametric analyses further elucidate the modulation of SR characteristics by three critical factors: non-Gaussian noise intensity parameters, noise correlation timescale and inter-node coupling strength. Finally, we explore the system’s size resonance properties.

Key words: non-Gaussian noise, bistable coupled network systems, statistical complexity measure, stochastic resonance

中图分类号:  (Stochastic analysis methods)

  • 05.10.Gg
05.40.-a (Fluctuation phenomena, random processes, noise, and Brownian motion)