在双通道信号检测领域,肯德尔秩相关系数(Kendall’s Tau, KT)作为一种检测器,对含脉冲噪声的信号具有显著的鲁棒性。然而,当通道间的噪声存在相关性时,KT的检测性能仍有待提升。为此,本文提出一种改进的肯德尔秩相关系数(Improved Kend...在双通道信号检测领域,肯德尔秩相关系数(Kendall’s Tau, KT)作为一种检测器,对含脉冲噪声的信号具有显著的鲁棒性。然而,当通道间的噪声存在相关性时,KT的检测性能仍有待提升。为此,本文提出一种改进的肯德尔秩相关系数(Improved Kendall’s Tau, IKT)检测器,在KT的基础上引入了阈值可调节的硬限幅函数。同时采用二元高斯混合模型(Gaussian Mixture Model, GMM)模拟两通道间噪声的相关性及脉冲特性,深入探讨了IKT在该模型下的统计性质,并建立了针对双通道高斯随机信号检测问题的虚警率和检测概率的解析式。通过蒙特卡罗实验与高斯噪声下性能最优的匹配滤波器(Matched Filter Detector, MFD)、脉冲噪声下具有鲁棒性的极性重合相关器(Polarity Coincidence Correlator, PCC)、KT的接收机工作特性(Receiver Operating Characteristic, ROC)曲线下面积(Area Under the Curve, AUC)进行比较,表明IKT在含相关性高斯噪声的信号检测中相较于PCC在AUC上表现出12.9%左右的提升,相较于KT的提升约为4.8%。在含相关性脉冲噪声的信号检测中相较于PCC的AUC提升约为8.3%,相较于KT的提升约为1.6%,从而验证了其优越性。In dual-channel signal detection, the Kendall’s Tau (KT) correlation coefficient is well-regarded for its robustness in handling signals affected by impulsive noise. However, its detection performance declines when there is noise correlation between channels. To address this limitation, this paper presents an Improved Kendall’s Tau (IKT) detector, which enhances the traditional KT by incorporating a threshold-adjustable hard limiting function. Furthermore, a bivariate Gaussian Mixture Model (GMM) is used to simulate the noise correlation and impulsive characteristics between the two channels. The statistical properties of IKT under this model are thoroughly analyzed, and analytical expressions for the false alarm rate and detection probability in dual-channel Gaussian random signal detection are derived. Monte Carlo simulations and comparisons with the matched filter detector (MFD), which is optimal for Gaussian noise, the polarity coincidence correlator (PCC), known for its robustness against impulsive noise, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for KT, are performed. The results show that in the presence of correlated Gaussian noise, IKT achieves approximately a 12.9% improvement in AUC over PCC and a 4.8 % improvement over KT. In the presence of correlated impulsive noise, IKT shows about an 8.3% improvement in AUC over PCC and a 1.6% improvement over KT, thereby validating its superiority.展开更多
Let{Xn;n≥1}be a sequence of i.i.d, random variables with finite variance,Q（n）be the related R/S statistics. It is proved that lim ε↓0 ε^2 ∑n=1 ^8 n log n/1 P{Q（n）≥ε√2n log log n}=2/1 EY^2,where Y=sup0≤t...Let{Xn;n≥1}be a sequence of i.i.d, random variables with finite variance,Q（n）be the related R/S statistics. It is proved that lim ε↓0 ε^2 ∑n=1 ^8 n log n/1 P{Q（n）≥ε√2n log log n}=2/1 EY^2,where Y=sup0≤t≤1B（t）-inf0≤t≤sB（t）,and B（t） is a Brownian bridge.展开更多
As the world's authoritative organization on energy information, the International Energy Agency (IEA), which was founded in 1974, releases Key World Energy Statistics every year from 1997 (hereinafter referred to...As the world's authoritative organization on energy information, the International Energy Agency (IEA), which was founded in 1974, releases Key World Energy Statistics every year from 1997 (hereinafter referred to as the "Key Data"). The "Key Data" released in 2007 announced the 2005 statistics, and also provided the 1973 statistics for comparison. From the published data, we can clearly find the development path and trend of the world energy and power industry. Also, China's strong development momentum, high- speed growth of energy consumption and the enormous challenges in the sustainable energy supply are especially noticeable. This paper reviewed the "Key Data" to perceive China's Energy Development. The analysis and interpretation of these data are purely from the author's point of view.展开更多
Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating du...Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response.This paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input data.The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties.The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic models.The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India.The proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of properties.Imprecise Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection efforts.Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes.The accurate importance ranking of properties was only possible via samples of large sizes.Further,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.展开更多
China has achieved new progress in education and has made headway in reform of the management system of higher education.In 1996。there were 1。032 universities and colleges and 1,138 institutions of higher learn-ing ...China has achieved new progress in education and has made headway in reform of the management system of higher education.In 1996。there were 1。032 universities and colleges and 1,138 institutions of higher learn-ing for adult education,22 and 18 fewer respectively than in 1995 due to read justment.展开更多
文摘在双通道信号检测领域,肯德尔秩相关系数(Kendall’s Tau, KT)作为一种检测器,对含脉冲噪声的信号具有显著的鲁棒性。然而,当通道间的噪声存在相关性时,KT的检测性能仍有待提升。为此,本文提出一种改进的肯德尔秩相关系数(Improved Kendall’s Tau, IKT)检测器,在KT的基础上引入了阈值可调节的硬限幅函数。同时采用二元高斯混合模型(Gaussian Mixture Model, GMM)模拟两通道间噪声的相关性及脉冲特性,深入探讨了IKT在该模型下的统计性质,并建立了针对双通道高斯随机信号检测问题的虚警率和检测概率的解析式。通过蒙特卡罗实验与高斯噪声下性能最优的匹配滤波器(Matched Filter Detector, MFD)、脉冲噪声下具有鲁棒性的极性重合相关器(Polarity Coincidence Correlator, PCC)、KT的接收机工作特性(Receiver Operating Characteristic, ROC)曲线下面积(Area Under the Curve, AUC)进行比较,表明IKT在含相关性高斯噪声的信号检测中相较于PCC在AUC上表现出12.9%左右的提升,相较于KT的提升约为4.8%。在含相关性脉冲噪声的信号检测中相较于PCC的AUC提升约为8.3%,相较于KT的提升约为1.6%,从而验证了其优越性。In dual-channel signal detection, the Kendall’s Tau (KT) correlation coefficient is well-regarded for its robustness in handling signals affected by impulsive noise. However, its detection performance declines when there is noise correlation between channels. To address this limitation, this paper presents an Improved Kendall’s Tau (IKT) detector, which enhances the traditional KT by incorporating a threshold-adjustable hard limiting function. Furthermore, a bivariate Gaussian Mixture Model (GMM) is used to simulate the noise correlation and impulsive characteristics between the two channels. The statistical properties of IKT under this model are thoroughly analyzed, and analytical expressions for the false alarm rate and detection probability in dual-channel Gaussian random signal detection are derived. Monte Carlo simulations and comparisons with the matched filter detector (MFD), which is optimal for Gaussian noise, the polarity coincidence correlator (PCC), known for its robustness against impulsive noise, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for KT, are performed. The results show that in the presence of correlated Gaussian noise, IKT achieves approximately a 12.9% improvement in AUC over PCC and a 4.8 % improvement over KT. In the presence of correlated impulsive noise, IKT shows about an 8.3% improvement in AUC over PCC and a 1.6% improvement over KT, thereby validating its superiority.
基金Supported by the Scientific and Technological Innovation Projects of Department of Education of Guangdong Province(2012KJCX0082)Science and Technology Projects of Guangdong Province(2011B090400623)Guangzhou Science and Technology Projects(12C42011563,11A11020499)
基金Project Supported by NSFC (10131040)SRFDP (2002335090)
文摘A law of iterated logarithm for R/S statistics with the help of the strong approximations of R/S statistics by functions of a Wiener process is shown.
文摘Let{Xn;n≥1}be a sequence of i.i.d, random variables with finite variance,Q（n）be the related R/S statistics. It is proved that lim ε↓0 ε^2 ∑n=1 ^8 n log n/1 P{Q（n）≥ε√2n log log n}=2/1 EY^2,where Y=sup0≤t≤1B（t）-inf0≤t≤sB（t）,and B（t） is a Brownian bridge.
文摘As the world's authoritative organization on energy information, the International Energy Agency (IEA), which was founded in 1974, releases Key World Energy Statistics every year from 1997 (hereinafter referred to as the "Key Data"). The "Key Data" released in 2007 announced the 2005 statistics, and also provided the 1973 statistics for comparison. From the published data, we can clearly find the development path and trend of the world energy and power industry. Also, China's strong development momentum, high- speed growth of energy consumption and the enormous challenges in the sustainable energy supply are especially noticeable. This paper reviewed the "Key Data" to perceive China's Energy Development. The analysis and interpretation of these data are purely from the author's point of view.
文摘Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response.This paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input data.The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties.The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic models.The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India.The proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of properties.Imprecise Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection efforts.Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes.The accurate importance ranking of properties was only possible via samples of large sizes.Further,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.
文摘China has achieved new progress in education and has made headway in reform of the management system of higher education.In 1996。there were 1。032 universities and colleges and 1,138 institutions of higher learn-ing for adult education,22 and 18 fewer respectively than in 1995 due to read justment.
