在线阅读 --自然科学版 2020年1期《基于信息论下阈值阵列模型中的阈上随机共振现象》
基于信息论下阈值阵列模型中的阈上随机共振现象--[在线阅读]
刘畅1, 王红梅2
1. 信阳职业技术学院 数学与计算机科学学院, 河南 信阳 464000;
2. 兰州交通大学 数理学院, 甘肃 兰州 730070
起止页码: 32--36页
DOI: 10.13763/j.cnki.jhebnu.nse.2020.01.005
摘要
研究了高斯混合噪声作用下阈值阵列模型中的阈上随机共振现象.通过建立阈值阵列模型,运用理论分析和数值仿真相结合的方法,分析了高斯混合噪声作用下高斯信号通过系统时的互信息.数值仿真表明,通过控制变量法,当阈值单元数目越多或者系统阈值越大时,阈上随机共振发生的现象更加明显.所得结论可以为进一步探索阈值阵列模型提供基础.

Suprathreshold Stochastic Resonance in Threshold Array Model Based on Information Theory
LIU Chang1, WANG Hongmei2
1. Department of Mathematics and Computed Sciences, Xinyang Vocational and Technical College, Henan Xinyang 464000, China;
2. School of Mathematics and Physics, Lanzhou Jiaotong University, Gansu Lanzhou 730070, China
Abstract:
Suprathreshold stochastic resonance (SSR) in the threshold array model under Gauss mixture noise is studied.Combining the theoretical analysis with numerical simulation,the mutual information of Gauss signal passing through the system under Gauss mixture noise is analyzed by establishing a threshold array model in this paper.The numerical simulation shows that the phenomenon of suprathreshold stochastic resonance will be more obvious when the number of threshold units of or the threreshold value of the system is larger by controlling variables.This study provides some idesa for further exploring threshold array model.

收稿日期: 2019-07-16
基金项目: 甘肃省自然科学基金(17JR5RA096)

参考文献:
[1]郑克.两种阈值网络系统中的随机共振现象研究[D].南京:南京邮电大学,2014. ZHENG Ke.The Research of Stochastic Resonance in Two Kinds of Threshold Network Systems[D].Nanjing:Nanjing University of Posts and Telecommunications,2014.
[2]侯鹏鹏.超阈值随机共振中的刺激条件信息研究[D].青岛:青岛大学,2017. HOU Pengpeng.Research on the Information of Stimulating Condition in the Random Resonance of Superthreshold Value[D].Qingdao:Qingdao University,2017.
[3]姜梦琦.阈值网络中基于互信息的随机共振研究[D].南京:南京邮电大学,2016. JIANG Mengqi.The Research of Stochastic Resonance in Threshold Network Based on Mutual Information[D].Nanjing:Nanjing University of Posts and Telecommunications,2016.
[4]李群伟.基于阈值随机共振系统的微弱信号增强与检测技术[D].西安:西安电子科技大学,2014. LI Qunwei.Slight Signal Enhancement and Detection Based on Threshold Random Resonance System[D].Xi'an:Xidian University,2014.
[5]许丽艳.加权超阈值随机共振的信号重构方法研究[D].青岛:青岛大学,2017. XU Liyan.Research on Signal Reconstruction Method of Weighted Super-threshold Random Resonance[D].Qingdao:Qingdao University,2017.
[6]王友国,刘沁雨.多阈值系统中高斯混合噪声改善信息的传输[J].计算机技术与发展,2011,21(4):120-122.doi:10.3969/j.issn.1673-629X.2011.04.031 WANG Youguo,LIU Qinyu.Transmission of Gaussian Mixed Noise Improvement Information in Multithreshold System[J].Computer Technology and Development,2011,21(4):120-122.
[7]王友国,刘洪伟,罗辑.基于互信息的多阈值系统中随机谐振现象研究[J].计算机技术与发展,2010,20(6):89-92.doi:10.3969/j.issn.1673-629X.2010.06.023 WANG Youguo,LIU Hongwei,LUO Ji.Stochastic Resonance in Multi-threshold Systems Based on Mutual Information[J].Computer Technology and Development,2010,20(6):89-92.
[8]张礁石,杨子贤,卢结成.阈值阵列模型下的超阈值随机共振信噪比增益[J].数据采集与处理,2013,28(2):226-230. ZHANG Jiaoshi,YANG Zixian,LU Jiecheng.High Threshold Random Resonance Signal-to-noise Gain Under Threshold Array Model[J].Data Collection and Processing,2013,28(2):226-230.
[9]GUO Yongfeng,TAN Jianguo.Suprathreshold Stochastic Resonance in Multilevel Threshold System Driven by Multiplicative and Additive Noises[J].Communications in Nonlinear Science and Numerical Stimulation,2013,18(10):2852-2858.doi:10.1016/j.cnsns.2013.02.006
[10]ZHOU Bingchang,MCDONNELL M D.Optimising Threshold Levels for Information Transmission in Binary Threshold Networks:Independent Multiplicative Noise on Each Threshold[J].Physica A:Statistical Mechanics and Its Applications,2015,419:659-667.doi:10.1016/j.physa.2014.10.074
[11]CHENG Chaojun,ZHOU Bingchang,GAO Xiao,et al.M-ary Suprathreshold Stochastic Resonance in Multilevel Threshold Systems with Signal-dependent Noise[J].Physica A:Statistical Mechanics and Its Applications,2017,479(1):48-56.doi:10.1016/j.physa.2017.03.010
[12]郭永峰,谭建国.一类非线性神经网络系统的超阈值随机共振现象[J].物理学报,2012,61(17):170502. GUO Yongfeng,TAN Jianguo.Superthreshold Random Resonance in a Class of Nonlinear Neural Network Systems[J].Journal of Physics,2012,61(17):170502.