[1]段江海,宋爱国,温秀兰,等.神经元中的随机共振及含噪周期方波脉冲信号的最优检测[J].东南大学学报(自然科学版),2003,33(3):328-330.[doi:10.3969/j.issn.1001-0505.2003.03.020]
 Duan Jianghai,Song Aiguo,Wen Xiulan,et al.Stochastic resonance in neuron and optimal detection of noisy periodic rectangular pulse trains[J].Journal of Southeast University (Natural Science Edition),2003,33(3):328-330.[doi:10.3969/j.issn.1001-0505.2003.03.020]
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神经元中的随机共振及含噪周期方波脉冲信号的最优检测()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
33
期数:
2003年第3期
页码:
328-330
栏目:
电子科学与工程
出版日期:
2003-05-20

文章信息/Info

Title:
Stochastic resonance in neuron and optimal detection of noisy periodic rectangular pulse trains
作者:
段江海 宋爱国 温秀兰 崔建伟
东南大学仪器科学与工程系,南京 210096
Author(s):
Duan Jianghai Song Aiguo Wen Xiulan Cui Jianwei
Department of Instrument Science and Technology, Southeast University, Nanjing 210096, China
关键词:
随机共振 神经元 信噪比增益 最优检测
Keywords:
stochastic resonance neuron SNR gain optimal detection
分类号:
TN215
DOI:
10.3969/j.issn.1001-0505.2003.03.020
摘要:
理论研究表明,神经元用于含噪周期方波脉冲信号传输时存在随机共振现象,信号的占空比和神经元的阈值对随机共振的影响有一定的规律.同时,可获得大于1的信噪比增益,这是线性系统不能实现的,因而可将神经元的应用推广到非线性信号处理领域.在此基础上,对应用神经元实现含噪周期方波脉冲信号检测的最优条件和最优特性进行了分析.最后,通过仿真实验验证了理论分析的正确性.
Abstract:
Neuron is demonstrated to have stochastic resonance(SR)by theoretic analysis when applied to the noisy periodic rectangular pulse trains signal transmission. The influence on SR of the parameters including periodic signal’s filling factor and neuron’s threshold is found to be regular. Significant performance that SNR gain is larger than one is available, which can’t be obtained by linear techniques. Therefore, neuron is applicable to nonlinear signal processing. On this basis, neuron is used to detect noisy periodic rectangular pulse trains. The conditions and the properties of optimal detection are analyzed. The results from experimental simulations prove the correctness of the theoretic analysis.

参考文献/References:

[1] Benzi R,Srutera A,Vulpiani A.The mechanism of stochastic resonance [J]. J Phys A,1981,14(11):453-457.
[2] Chapeau-Blondeau F,Godivier X.Theory of stochastic resonance in signal transmission by static nonlinear systems [J].Phys Rev E,1997,55(2):1478-1495.
[3] Chapeau-Blondeau F.Input output gains for signal in noise in stochastic resonance [J]. Phys Lett A,1997,232(1):41-48.
[4] Chapeau-Blondeau F.Stochastic resonance and optimal detection of pulse trains by threshold devices [J]. Digital Signal Processing,1999,9:162-177.
[5] Chapeau-Blondeau F.Periodic and aperiodic stochastic resonance with output signal-to-noise ratio exceeding that at the input [J].Int J of Bifurcation and Chaos, 1999,9(1):267-272.

相似文献/References:

[1]约尔钦·宁克段江海宋爱国吴涓.随机共振神经元利用噪声辅助进行信号传输特性分析[J].东南大学学报(自然科学版),2005,35(5):710.[doi:10.3969/j.issn.1001-0505.2005.05.012]
 Joachim Ninke,Duan Jianghai,Song Aiguo,et al.Analysis on noise-assisted signal transmission in neurons based on stochastic resonance[J].Journal of Southeast University (Natural Science Edition),2005,35(3):710.[doi:10.3969/j.issn.1001-0505.2005.05.012]

备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(69875004).
作者简介: 段江海(1977—),男, 博士生; 宋爱国(联系人),男,博士,教授,博士生导师, a.g.song@seu.edu.cn.
更新日期/Last Update: 2003-05-20