计算数学
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计算数学  2017, Vol. 39 Issue (4): 339-350    DOI:
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高维带宽有限随机信号从平均过采样的指数阶逼近
陈文健1, 张海樟2
1. 烟台大学数学与信息科学学院, 烟台 264005;
2. 中山大学数据科学与计算机学院广东省计算科学重点实验室, 广州 510275
EXPONENTIAL APPROXIMATION OF MULTIVARIATE BANDLIMITED STOCHASTIC SIGNALS FROM AVERAGE OVERSAMPLING
Chen Wenjian1, Zhang Haizhang2
1. School of Mathematics and Information Sciences, Yantai University, Yantai 264005, China;
2. School of Mathematics and Computational Science and Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, China
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摘要 本文中我们主要考虑利用有限的平均过采样值来重构高维带宽有限随机信号.我们给出了一个能够达到指数阶衰减逼近能力的重构算法.对于一般型和乘积型的采样测度,我们分别给出了对应的重构算法和指数阶衰减的重构误差估计.
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关键词高维带宽有限宽平稳随机过程   平均过采样   指数阶衰减逼近误差     
Abstract: In this note, we mainly consider reconstructing multivariate bandlimited wide stationary stochastic signals from finite average oversampling. We derive a reconstruction algorithm which attains the exponentially-decaying reconstruction rate. When the sampling measure is of general type or tensor-product type, we all derive an exponentially-decaying reconstruction error estimate.
Key wordsmultivariate bandlimited wide stationary stochastic processes   average oversampling   exponentially-decaying approximation error   
收稿日期: 2016-12-10;
基金资助:

山东省自然科学基金(ZR2016AP11);国家自然科学基金(11571377,11222103).

引用本文:   
. 高维带宽有限随机信号从平均过采样的指数阶逼近[J]. 计算数学, 2017, 39(4): 339-350.
. EXPONENTIAL APPROXIMATION OF MULTIVARIATE BANDLIMITED STOCHASTIC SIGNALS FROM AVERAGE OVERSAMPLING[J]. Mathematica Numerica Sinica, 2017, 39(4): 339-350.
 
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