数据采集与处理2013，Vol.28Issue(2)：226-230,5.
阈值阵列模型下的超阈值随机共振信噪比增益
Signal-to-Noise Ratio Gain of Suprathreshold Stochastic Resonance Based on Threshold Array Model
摘要
Abstract
The threshold-array model is presented to study suprathreshold stochastic resonance (SSR) phenomenon. The analysis of the presented model proves 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 SSR with periodic input, the statistical properties of the output process of the threshold-array model are evaluated. With a fixed input signal-to-noise ratio (SNR), 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.关键词
超阈值随机共振/阈值阵列模型/集总平均/信噪比增益Key words
suprathreshold stochastic resonance/ threshold array model/ ensemble averaging/ SNR gain分类
信息技术与安全科学引用本文复制引用
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):226-230,5.基金项目
塔里木油田项目(971009090126)资助项目. （971009090126）
