SPARSITY相关论文
Recent technological advancements and developments have led to a dramatic increase in the amount of high-dimensional dat......
The compressed sensing matrices based on affine symplectic space are constructed.Meanwhile,a comparison is made with the......
The sparsity which is implicit in MR images is exploited to significantly undersample k-space.According to the developed......
為了建立多構面的使用者輪廓，本研究採用多準則評分(Multi-criteria Ratings)作為電影喜好蒐集，並且以統 計方法的複迴歸分析將迴歸......
Comparing mean vectors of high dimensional data and large covariance matrices has important applications in modern genom......
Recently,various methods have been proposed for estimation and model selection in highdimensional statistical settings....
Estimating signals in the presence of a large amount of noise is a challenging problem in high-dimensional normal mean e......
In this paper,we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sampl......
We consider the problem of uncertainty assessment for low dimensional components in high dimensional models.Specifically......
基于图像压缩传感理论, 在手动式光学单点成像系统的基础上研究了自动式光学单点成像系统。主要介绍了系统中自动编码转盘的设计以......
The influence of the sparsity of random speckle illumination on traditional ghost imaging(GI) and GI via sparsity constr......
Based on the multivariate mean-shift regression model,we propose a new sparse reduced-rank regression approach to achiev......
Sparse decomposition is one of the core issue of compressive sensing ghost image.At this stage,traditional methods s......
The two-sided rank-one (TR1) update method was introduced by Griewank and Walther (2002) for solving nonlinear equations......
The influence of the sparsity of random speckle illumination on traditional ghost imaging[GI]and GI via sparsity constra......
Periodicity is one of the most common phenomena in the physical world. The problem of periodicity analysis (or period de......
Geometric changes present a number of difficulties in deformable image registration. In this paper, we propose a global ......
,High resolution inverse synthetic aperture radar imaging of three-axis-stabilized space target by e
The development of inverse synthetic aperture radar (ISAR) imaging techniques is of notable significance for monitoring,......
Recent advances in various fields such as telecommunications,biomedicine and economics,among others,have created enormou......
Multispectral image denoising is a basic problem whose results affect subsequent processes such as target detection and ......
为了有效解决稀疏度未知的压缩信号快速重构问题,提出了一种适应范围较广、效率突出的信号重构方案.在该方案中,压缩信号的上下界......
该文从挂篮荷载计算、施工流程、支座及临时固结施工、挂篮安装及试验、合拢段施工、模板制作安装、钢筋安装、混凝土的浇筑及养生......
为探究吕家坨井田地质构造格局,根据钻孔勘探资料,采用分形理论和趋势面分析方法,研究了井田7......
为探究吕家坨井田地质构造格局,根据钻孔勘探资料,采用分形理论和趋势面分析方法,研究了井田7......
Based on the compressive sensing,a novel algorithm is proposed to solve reconstruction problem under sparsity assumption......
基于稀疏性的高光谱解混是近年来高光谱混合像元分解的研究热点。主要研究了L1正则化的高光谱混合像元分解算法。首先分析了L1正则......
运用传统的奈奎斯特定理对电力系统中的谐波信号进行采样将会产生极其庞大的数据量，而全新的压缩感知理论突破了传统采样定理的限制......
The computational efficiency of numerical solution of linear algebraic equations in finite elements can be improved in t......
压缩感知重构信号时,在感知过程中如何选定支撑集对算法的重构性能至关重要。基于压缩采样匹配(CoSaMP)重构算法,引入Dice系数匹配......
用户-项目评分数据集的高维稀疏性使得传统的协同过滤处于＂维度困境＂。运用降维技术的特征变换方法的协同过滤算法虽然缩减用户-项目......
近年来,K-SVD算法在功能磁共振成像（functional magnetic resonance imaging,f MRI）数据分析方法的研究中越来越受到关注.在本文中,......
已有的基于压缩感知的核磁共振图像重构算法仅利用了数据的稀疏性或矩阵的低秩性,并没有充分利用图像数据的相关性先验知识。针对......
针对L_1范数多核学习方法产生核权重的稀疏解时可能会导致有用信息的丢失和泛化性能退化、L_p范数多核学习方法产生核权重的非稀疏......
评分数据的极端稀疏性是制约协同过滤(CF)算法在电子商务推荐中有效应用的关键瓶颈。为此,提出一种新颖的隐空间多源迁移协同过滤(......
传统支持向量机通常关注于数据分布的边缘样本,支持向量通常在这些边缘样本中产生。本文提出一个新的支持向量算法,该算法的支持向......
由于用户评分的偏好性,及其稀疏的评分矩阵,导致对目标用户的近邻无法进行准确的搜索,使得推荐结果不尽如人意.本文提出了一种联合......
应用尺度自适应三维Shearlet变换压制多炮地震数据随机噪声,通过将多炮数据变换到三维Shearlet域,充分考虑单炮记录及其间的相关性......
电容触摸屏是一种应用非常广泛的电子产品,但常规方法实现大屏幕电容屏的快速触控检测需要的硬件电路成本昂贵、且能耗高.首先给出......
针对海面舰船等具有一定空间稀疏性的合成孔径雷达成像场景,提出了一种稀疏场景目标的距离像峰值聚类分割成像方法。首先采用小波......
图像处理领域基本问题之一是图像的稀疏表示,并且图像的有效表示是图像处理应用开展的基础,图像表示的有效性是指用很少的数据捕获......
地震反褶积是一种重要的压缩地震子波、提高薄层纵向分辨率的地震数据处理方法。在层状地层的假设下,反射系数可视作稀疏的脉冲序......
压缩感知重构图像时,重构图像的失真率会随着稀疏度的增大而增大。文章基于压缩感知的正交匹配追踪(OMP)重构算法,引入离散余弦变......
针对当前方法重构视觉图像时,存在峰值信噪比低、重构时间长和图像分辨率低的问题,提出基于稀疏度自适应的视觉图像三维清晰重构方......
大数据时代,从大量数据中寻找出数据潜在的关联受到广泛关注。双聚类是指对行和列同时聚类,对矩阵局部进行搜索,旨在对高维数据中......
非负矩阵分解(NMF)由于其非负性和分块表征能力,使得该算法大量的应用于机器学习和信号处理等相关领域。经典NMF与线性混合的高光......
Based on the compressive sensing,a novel algorithm is proposed to solve reconstruction problem under sparsity assumption......
利用合成孔径雷达（SAR）图像中目标的后向散射特性和目标散射中心的理论,分析了SAR图像数据稀疏性的成因。指出SAR图像的稀疏性与典型......
针对评分数据稀疏性和用户冷启动所导致的协同过滤推荐系统的准确度与覆盖率较低的问题,文中融合显性信任和隐性信任因素,提出了一......
变分正则化方法基本思想是分析和把握图像的先验知识,将图像的正则化复原问题转变成极小化能量泛函问题。根据图像的有界变差和稀......
稀疏表示近年来在模式识别领域已经取得了成功的应用,如目标探测和分类。稀疏保留投影(SPP)算法是基于稀疏表示理论所提出的一种特......
