阈值阵列模型下的超阈值随机共振信噪比增益
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中国科学技术大学

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塔里木油田项目编号971009090126


Study on Signal-to-noise Ratio Gain of Suprathreshold Stochastic Resonance based on Threshold Array Model
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University of Science and Technology of China

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    摘要:

    研究了阈值阵列模型和超阈值随机共振现象。对该模型进行剖析,认为阈值阵列系统可以分解为单个阈值系统与集总平均器的级联。为了研究周期输入下的超阈值随机共振现象,理论分析了周期输入下的阈值阵列模型输出随机过程的统计特性,以输出信噪比增益作为随机共振的测度,固定输入信噪比,观测输出信噪比增益相对于阈值噪声方差的变化规律。证实当输入噪声为高斯噪声时,在阈值阵列系统中加入统计独立的高斯白噪声可使输出信噪比增益大于1,当输入噪声为非高斯噪声时,可获得更高的输出信噪比增益。

    Abstract:

    The threshold-array model is presented to study Suprathreshold Stochastic Resonance(SSR) phenomenon . Analysis of the model proves that that the threshold-array system can be decomposed into a cascade of a single threshold system and an ensemble averager. In order to study the Suprathreshold Stochastic Resonance with periodic input, the statistical properties of the output process of the threshold-array model is evaluated. With a fixed input signal-to-noise ratio, the output SNR Gain of the model varies in a non-monotonic way when injecting independent threshold noises into the array. If the input noise is Gaussian, when adding independent Gaussian white threshold noises into the array, a SNR Gain larger than unity can be obtained. Moreover, when the input noise is non-Gaussian, there will be a better SNR Gain.

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张礁石.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-

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历史
  • 收稿日期:2011-12-08
  • 最后修改日期:2012-05-14
  • 录用日期:2012-05-14
  • 在线发布日期: 2013-04-25