This paper presents a small perturbation Cramer method for obtaining the large deviation principle of a family of measures (β,ε> 0) on a topological vector space. As an application, we obtain the moderate deviati...This paper presents a small perturbation Cramer method for obtaining the large deviation principle of a family of measures (β,ε> 0) on a topological vector space. As an application, we obtain the moderate deviation estimations for uniformly ergodic Markov processes.展开更多
This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and t...This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.展开更多
We discuss the incomplete semi-iterative method (ISIM) for an approximate solution of a linear fixed point equations x=Tx+c with a bounded linear operator T acting on a complex Banach space X such that its resolvent h...We discuss the incomplete semi-iterative method (ISIM) for an approximate solution of a linear fixed point equations x=Tx+c with a bounded linear operator T acting on a complex Banach space X such that its resolvent has a pole of order k at the point 1. Sufficient conditions for the convergence of ISIM to a solution of x=Tx+c, where c belongs to the range space of R(I-T) k, are established. We show that the ISIM has an attractive feature that it is usually convergent even when the spectral radius of the operator T is greater than 1 and Ind 1T≥1. Applications in finite Markov chain is considered and illustrative examples are reported, showing the convergence rate of the ISIM is very high.展开更多
为了提高合成孔径雷达(synthetic aperture radar,SAR)影像变化检测的精度,提出一种基于变分法与马尔可夫随机场模糊局部信息聚类(Markov random field fuzzy local information C-means clustering,MRFFLICM)的SAR影像变化检测方法。...为了提高合成孔径雷达(synthetic aperture radar,SAR)影像变化检测的精度,提出一种基于变分法与马尔可夫随机场模糊局部信息聚类(Markov random field fuzzy local information C-means clustering,MRFFLICM)的SAR影像变化检测方法。首先融合对数比影像和对数均值比影像来构建差异影像;然后采用变分去噪模型去除差异影像的噪声;最后利用马尔可夫随机场将空间邻域信息引入到模糊局部信息C均值聚类算法中,提高聚类的性能。对两组不同时相真实SAR影像数据进行对比实验,结果表明,提出的变分去噪方法能够避免去除微小变化区域,有效抑制SAR影像的斑点噪声,同时MRFFLICM方法可以有效提高变化检测的精度,提升了变化检测方法的适应性。展开更多
文摘This paper presents a small perturbation Cramer method for obtaining the large deviation principle of a family of measures (β,ε> 0) on a topological vector space. As an application, we obtain the moderate deviation estimations for uniformly ergodic Markov processes.
文摘This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.
基金Project1 990 1 0 0 6 supported by National Natural Science Foundation of China,Doctoral Foundation of China,Chi-na Scholarship council and Laboratory of Computational Physics in Beijing of Chinathe second author is also supportedby the State Major Key
文摘We discuss the incomplete semi-iterative method (ISIM) for an approximate solution of a linear fixed point equations x=Tx+c with a bounded linear operator T acting on a complex Banach space X such that its resolvent has a pole of order k at the point 1. Sufficient conditions for the convergence of ISIM to a solution of x=Tx+c, where c belongs to the range space of R(I-T) k, are established. We show that the ISIM has an attractive feature that it is usually convergent even when the spectral radius of the operator T is greater than 1 and Ind 1T≥1. Applications in finite Markov chain is considered and illustrative examples are reported, showing the convergence rate of the ISIM is very high.
文摘为了提高合成孔径雷达(synthetic aperture radar,SAR)影像变化检测的精度,提出一种基于变分法与马尔可夫随机场模糊局部信息聚类(Markov random field fuzzy local information C-means clustering,MRFFLICM)的SAR影像变化检测方法。首先融合对数比影像和对数均值比影像来构建差异影像;然后采用变分去噪模型去除差异影像的噪声;最后利用马尔可夫随机场将空间邻域信息引入到模糊局部信息C均值聚类算法中,提高聚类的性能。对两组不同时相真实SAR影像数据进行对比实验,结果表明,提出的变分去噪方法能够避免去除微小变化区域,有效抑制SAR影像的斑点噪声,同时MRFFLICM方法可以有效提高变化检测的精度,提升了变化检测方法的适应性。
