SUB-GAUSSIAN

作品数：6被引量：2H指数：1
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相关机构：华中师范大学更多>>
相关期刊：《Journal of Mathematical Research with Applications》《Journal of Computational Mathematics》《Acta Mathematica Scientia》《Probability, Uncertainty and Quantitative Risk》更多>>
相关基金：国家自然科学基金更多>>
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Optimal Estimation of High-Dimensional Covariance Matrices with Missing and Noisy Data
《Advances in Pure Mathematics》2024年第4期214-227,共14页Meiyin Wang Wanzhou Ye 
The estimation of covariance matrices is very important in many fields, such as statistics. In real applications, data are frequently influenced by high dimensions and noise. However, most relevant studies are based o...
关键词：High-Dimensional Covariance Matrix Missing Data Sub-Gaussian Noise Optimal Estimation 
The Recovery Guarantee for Orthogonal Matching Pursuit Method to Reconstruct Sparse Polynomials
《Numerical Mathematics(Theory,Methods and Applications)》2022年第3期793-818,共26页Aitong Huang Renzhong Feng Sanpeng Zheng 
supported by the National Natural Science Foundation of China(Grant No.12071019).
Orthogonal matching pursuit(OMP for short)algorithm is a popular method of sparse signal recovery in compressed sensing.This paper applies OMP to the sparse polynomial reconstruction problem.Distinguishing from classi...
关键词：Reconstruction of sparse polynomial uniformly bounded orthogonal system orthogonal matching pursuit method probability of successful reconstruction sub-Gaussian random variable 
Improved Hoeffding inequality for dependent bounded or sub-Gaussian random variables
《Probability, Uncertainty and Quantitative Risk》2021年第1期53-60,共8页Yuta Tanoue 
This work was supported by JSPS Grant-in-Aid for Young Scientists(Grant No.18K12873);Waseda University Grants for Special Research Projects(“Tokutei Kadai”)(Grant No.2019C-688).
When addressing various financial problems,such as estimating stock portfolio risk,it is necessary to derive the distribution of the sum of the dependent random variables.Although deriving this distribution requires i...
关键词：α-mixing coefficient Hoeffding inequality BOUNDED SUB-GAUSSIAN 
A Refined Non-Asymptotic Tail Bound of Sub-Gaussian Matrix
《Journal of Mathematical Research with Applications》2020年第5期543-550,共8页Xianjie GAO Chao ZHANG Hongwei ZHANG 
Supported by the Fundamental Research Funds for the Central Universities(Grant No.DUT20LK38)。
In this paper,we obtain a refined non-asymptotic tail bound for the largest singular value(the soft edge)of sub-Gaussian matrix.As an application,we use the obtained theorem to compute the tail bound of the Gaussian T...
关键词：non-asymptotic theory largest singular value tail bound sub-Gaussian matrix 
A BALANCED OVERSAMPLING FINITE ELEMENT METHOD FOR ELLIPTIC PROBLEMS WITH OBSERVATIONAL BOUNDARY DATA被引量：1
《Journal of Computational Mathematics》2020年第2期355-374,共20页Zhiming Chen Rui Tuo Wenlong Zhang 
This work was supported in part by the National Center for Mathematics and Interdisciplinary Sciences,CAS and China NSF under the grant 118311061 and 11501551.
In this paper we propose a finite element method for solving elliptic equations with observational Dirichlet boundary data which may subject to random noises.The method is based on the weak formulation of Lagrangian m...
关键词：Observational boundary data Elliptic equation Sub-Gaussian random variable. 
STABLE SUB-GAUSSIAN MODELS CONSTRUCTED BY POISSON PROCESSES被引量：1
《Acta Mathematica Scientia》2011年第5期1945-1958,共14页戴洪帅 李育强 
supported by National Natural Science Foundation of China (10901054)
In this paper, we first prove that one-parameter standard α-stable sub-Gaussian processes can be approximated by processes constructed by integrals based on the Poisson process with random intensity. Then we extend t...
关键词：stable sub-Gaussian process weak convergence Poisson process Riemann integral 
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