This paper studies the value distribution of random analytic Dirichlet series f(s) = Zn()e-sn, where {Zn} is a sequence of independent random variables, n = 1 with moments zero, such that infE{Zn}/E1/2{Zn2≥ α > ...This paper studies the value distribution of random analytic Dirichlet series f(s) = Zn()e-sn, where {Zn} is a sequence of independent random variables, n = 1 with moments zero, such that infE{Zn}/E1/2{Zn2≥ α > 0. Suppose [h*(σ)]2 = n converges for any α > 0, and diverges for = 0. It is shown that if = ρ E (0, ), then with probability one, where β is a constant depending only upon the constant α.展开更多
AIM: To propose a new meta-analysis method for bivariate P value which account for the paired structure.METHODS: Studies that look to test two different features from the same sample gives rise to bivariate P value.A ...AIM: To propose a new meta-analysis method for bivariate P value which account for the paired structure.METHODS: Studies that look to test two different features from the same sample gives rise to bivariate P value.A relevant example of this is testing for periodicity as well expression from time-course gene expression studies.Kocak et al(2010) uses George and Mudholkar'(1983) "Difference of Two Logit-Sums" method to pool bivariate P value across independent experiments,assuming independence within a pair.As bivariate P value need not to be independent within a given study,we propose a new meta-analysis approach for pooling bivariate P value across independent experiments,which accounts for potential correlation between paired P-values.We compare the "Difference of Two Logit Sums"method with our novel approach in terms of their sensitivity and specificity through extensive simulations by generating P value samples from most commonly used tests namely,Z test,t test,chi-square test,and F test,with varying sample sizes and correlation structure.RESULTS: The simulations results showed that our new meta-analysis approach for correlated and uncorrelated bivariate P value has much more desirable sensitivity and specificity features compared to the existing method,which treats each member of the paired P value as independent.We also compare these meta-analysis approaches on bivariate P value from periodicity and expression tests of 4936 S.Pombe genes from 10 independent time-course experiments and we showed that our new approach ranks the periodic,conserved,and cycling genes significantly higher,and detects many more periodic,"conserved" and "cycling" genes among the top 100 genes,compared to the ‘Difference of Two Logit-Sums' method.Finally,we used our metaanalytic approach to compare the relative evidence in the association of pre-term birth with preschool wheezing versus pre-school asthma.CONCLUSION: The new meta-analysis method has much better sensitivity and specific characteristics compared to the "Difference of Two-Logit Sums" method and it is not computationally more expensive.展开更多
A new method to extract person-independent expression feature based on higher-order singular value decomposition （HOSVD） is proposed for facial expression recognition. Based on the assumption that similar persons ha...A new method to extract person-independent expression feature based on higher-order singular value decomposition （HOSVD） is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and hence become less person-dependent. The proposed method is tested on Cohn-Kanade facial expression database and Japanese female facial expression （JAFFE） database. Person-independent experimental results show the superiority of the proposed method over the existing methods.展开更多
目的:为实现从母体腹壁混合信号中提取高信噪比和波形清晰的胎儿心电信号,提出一种融合核主成分分析(kernel principal component analysis,KPCA)、快速独立成分分析(fast independent component analysis,FastICA)及奇异值分解(singula...目的:为实现从母体腹壁混合信号中提取高信噪比和波形清晰的胎儿心电信号,提出一种融合核主成分分析(kernel principal component analysis,KPCA)、快速独立成分分析(fast independent component analysis,FastICA)及奇异值分解(singular value decomposition,SVD)的胎儿心电信号提取算法。方法:首先,采用KPCA对母体心电信号进行降维,再利用改进的基于负熵的FastICA处理降维后的数据,得到独立成分。随后,引入样本熵进行信号通道选择,挑选出包含最多母体信息的信号通道。在选中的母体通道上进行SVD,得到母体心电信号的近似估计,再用腹壁源信号减去该信号得到胎儿心电的初步估计。最后,采用改进的基于负熵的FastICA成功分离出纯净的胎儿心电信号。在腹部和直接胎儿心电图数据库(Abdominal and Direct Fetal Electrocardiogram Database,ADFECGDB)和PhysioNet 2013挑战赛数据库中对提出的算法进行验证。结果:提出的算法在主观视觉效果和客观评价指标上都表现出优越的性能。在ADFECGDB数据库中,胎儿QRS复合波检测的敏感度、阳性预测值和F1值分别为99.74%、98.85%和99.30%;在PhysioNet 2013挑战赛数据库中,胎儿QRS复合波检测的敏感度、阳性预测值和F1值分别为99.10%、97.87%和98.48%。结论:融合KPCA、FastICA及SVD的胎儿心电信号提取算法在提取胎儿心电信号的同时有效处理了附加噪声,为胎儿疾病的早期诊断提供了有力支持。展开更多
基金Project supported by the National Natural Science Foundationof China
文摘This paper studies the value distribution of random analytic Dirichlet series f(s) = Zn()e-sn, where {Zn} is a sequence of independent random variables, n = 1 with moments zero, such that infE{Zn}/E1/2{Zn2≥ α > 0. Suppose [h*(σ)]2 = n converges for any α > 0, and diverges for = 0. It is shown that if = ρ E (0, ), then with probability one, where β is a constant depending only upon the constant α.
文摘AIM: To propose a new meta-analysis method for bivariate P value which account for the paired structure.METHODS: Studies that look to test two different features from the same sample gives rise to bivariate P value.A relevant example of this is testing for periodicity as well expression from time-course gene expression studies.Kocak et al(2010) uses George and Mudholkar'(1983) "Difference of Two Logit-Sums" method to pool bivariate P value across independent experiments,assuming independence within a pair.As bivariate P value need not to be independent within a given study,we propose a new meta-analysis approach for pooling bivariate P value across independent experiments,which accounts for potential correlation between paired P-values.We compare the "Difference of Two Logit Sums"method with our novel approach in terms of their sensitivity and specificity through extensive simulations by generating P value samples from most commonly used tests namely,Z test,t test,chi-square test,and F test,with varying sample sizes and correlation structure.RESULTS: The simulations results showed that our new meta-analysis approach for correlated and uncorrelated bivariate P value has much more desirable sensitivity and specificity features compared to the existing method,which treats each member of the paired P value as independent.We also compare these meta-analysis approaches on bivariate P value from periodicity and expression tests of 4936 S.Pombe genes from 10 independent time-course experiments and we showed that our new approach ranks the periodic,conserved,and cycling genes significantly higher,and detects many more periodic,"conserved" and "cycling" genes among the top 100 genes,compared to the ‘Difference of Two Logit-Sums' method.Finally,we used our metaanalytic approach to compare the relative evidence in the association of pre-term birth with preschool wheezing versus pre-school asthma.CONCLUSION: The new meta-analysis method has much better sensitivity and specific characteristics compared to the "Difference of Two-Logit Sums" method and it is not computationally more expensive.
基金supported by National Natural Science Foundation of China (6087208460940008)+2 种基金Beijing Training Programming Foundation for the Talents (20081D1600300343)Excellent Young Scholar Research Fund of Beijing Institute of Technology (2007Y0305)Fundamental Research Foundation of Beijing Institute of Technology (20080342005)
文摘A new method to extract person-independent expression feature based on higher-order singular value decomposition （HOSVD） is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and hence become less person-dependent. The proposed method is tested on Cohn-Kanade facial expression database and Japanese female facial expression （JAFFE） database. Person-independent experimental results show the superiority of the proposed method over the existing methods.
文摘目的:为实现从母体腹壁混合信号中提取高信噪比和波形清晰的胎儿心电信号,提出一种融合核主成分分析(kernel principal component analysis,KPCA)、快速独立成分分析(fast independent component analysis,FastICA)及奇异值分解(singular value decomposition,SVD)的胎儿心电信号提取算法。方法:首先,采用KPCA对母体心电信号进行降维,再利用改进的基于负熵的FastICA处理降维后的数据,得到独立成分。随后,引入样本熵进行信号通道选择,挑选出包含最多母体信息的信号通道。在选中的母体通道上进行SVD,得到母体心电信号的近似估计,再用腹壁源信号减去该信号得到胎儿心电的初步估计。最后,采用改进的基于负熵的FastICA成功分离出纯净的胎儿心电信号。在腹部和直接胎儿心电图数据库(Abdominal and Direct Fetal Electrocardiogram Database,ADFECGDB)和PhysioNet 2013挑战赛数据库中对提出的算法进行验证。结果:提出的算法在主观视觉效果和客观评价指标上都表现出优越的性能。在ADFECGDB数据库中,胎儿QRS复合波检测的敏感度、阳性预测值和F1值分别为99.74%、98.85%和99.30%;在PhysioNet 2013挑战赛数据库中,胎儿QRS复合波检测的敏感度、阳性预测值和F1值分别为99.10%、97.87%和98.48%。结论:融合KPCA、FastICA及SVD的胎儿心电信号提取算法在提取胎儿心电信号的同时有效处理了附加噪声,为胎儿疾病的早期诊断提供了有力支持。
