摘要
在Levy噪声的驱动下,提出一种参数可调的二维三维随机共振(Two-dimensional Tristable Stochastic Resonance,TDTSR)系统,以平均信噪比增益(Mean Signal-to-noise Ratio Gain,MSNRG)为衡量指标,对系统参数进行寻优,采用ChamberMallows-Stuck(CMS)算法和耦合4阶龙格-库塔(Runge-kutta)算法相结合求解系统输出。首先,通过研究系统等效势函数,分析粒子跃迁路径和随机共振能量转换现象。然后,分析Levy噪声对各个参数的影响,确定其参数数值。此外,以MSNRG为系统衡量指标,将一维三稳随机共振(One-dimensional Tristable Stochastic Resonance,ODTSR)系统进行对比,结果表明TDTSR系统的MSNRG大于ODTSR系统。最后,将两种系统应用于微弱信号检测,并采用自适应算法对系统参数进行优化,实验结果表明,TDTSR系统优于ODTSR系统。此系统对微弱信号的检测具有重要的理论意义和实用价值。
Driven by Levy noise,a Two-dimensional Tristable Stochastic Resonance(TDTSR)system with adjustable parameters is proposed.With the Mean Signal-to-noise Ratio Gain(MSNRG)as the measure index,the adaptive algorithms are used to optimize the system parameters.The ChamberMallows Stuck(CMS)algorithm and coupled 4th order Runge Kutta algorithm are combined to solve the system output.Firstly,by studying the equivalent potential function of the system,the phenomena of particle transition paths and stochastic resonance energy conversion are analyzed.Then,the influence of various parameters of Levy noise is analyzed and its parameter values are determined.In addition,using MSNRG as a system metric,a comparison is made between the TDTSR system and the One-Dimensional Tristable Stochastic Resonance(ODTSR)system.The results show that the MSNRG of the TDTSR system is greater than that of the ODTSR system.Finally,the two systems are applied to weak signal detection and the adaptive algorithm is used to optimize system parameters.The experimental results show that the TDTSR system is superior to the ODTSR system.This system has important theoretical significance and practical value for the detection of weak signals.
作者
侯帅楠
殷利平
李涛
HOU Shuainan;YIN Liping;LI Tao(School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044,China;Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China)
出处
《噪声与振动控制》
北大核心
2025年第4期157-163,共7页
Noise and Vibration Control
基金
国家自然科学基金资助项目(61573190,61973168)。
关键词
声学
随机共振
Levy噪声
微弱信号检测
信噪比
势函数
acoustics
stochastic resonance
Levy noise
weak noise detection
signal to noise ratio
potential function
