随机共振
分叉
李雅普诺夫指数
数学
噪音(视频)
统计物理学
控制理论(社会学)
噪音的颜色
分岔理论
光谱密度
数学分析
非线性系统
白噪声
物理
量子力学
计算机科学
统计
图像(数学)
人工智能
控制(管理)
作者
Yanxia Zhang,Yanfei Jin,Pengfei Xu
出处
期刊:Chaos
[American Institute of Physics]
日期:2019-02-01
卷期号:29 (2)
被引量:35
摘要
Stochastic resonance (SR) and stochastic bifurcations are investigated numerically in a nonlinear tri-stable system driven by colored noise and a harmonic excitation. The power spectral density, signal-to-noise ratio, stationary probability density (SPD), and largest Lyapunov exponent (LLE) are calculated to quantify SR, P-bifurcation, and D-bifurcation, respectively. The effects of system parameters, such as noise intensity and correlation time, well-depth ratio, and damping coefficient, on SR and stochastic bifurcations are explored. Numerical results show that both noise-induced suppression and SR can be observed in this system. The SPD changes from bimodal to trimodal and then to the unimodal structure by choosing well-depth ratio, correlation time, and noise intensity as bifurcation parameters, which shows the occurrence of stochastic P-bifurcation. The stochastic D-bifurcation is found through the calculation of LLE. Moreover, the relationship between SR and stochastic bifurcation is explored thoroughly. It indicates that the optimal SR occurs near D-bifurcation and can be realized with weak chaos by adjusting the proper parameters. Finally, the tri-stable energy harvester is chosen as an example to show the improvement of the system performance by exploiting SR and stochastic bifurcations.
科研通智能强力驱动
Strongly Powered by AbleSci AI