基于支持向量机混合采样的不平衡数据分类方法

利用传统支持向量机(SVM)对不平衡数据进行分类时,由于真实的少数类支持向量样本过少且难以被识别,造成了分类时效果不是很理想.针对这一问题,提出了一种基于支持向量机混合采样的不平衡数据分类方法(BSMS).该方法首先对经过支持向量机分类的原始不平衡数据按照所处位置的不同划分为支持向量区(SV),多数类非支持向量区(MN...     

Experimental Evaluation of Undersampling Schemes for Electron Tomography of Nanoparticles

One of the emerging challenges in the field of 3D characterization of nanoparticles by electron tomography is to avoid degradation and deformation of the samples during the acquisition of a tilt series. In order to reduce the required electron dose, various undersampling approaches have been proposed. These methods include lowering the number of 2D projection images, reducing the probe current during the acquisition, and scanning a smaller number of pixels in the 2D images. A comparison is made between these approaches based on tilt series acquired for a gold nanoparticle.     

Theories to support method development in comprehensive two-dimensional liquid chromatography--a review

On-line comprehensive two-dimensional liquid chromatography techniques promise to resolve samples that current one-dimensional liquid chromatography methods cannot adequately deal with. To make full use of the potential of two-dimensional liquid chromatography, optimization is required. Optimization of two-dimensional liquid chromatography is a relatively new yet important research topic the aim of which is to predict combinations of stationary and mobile phases, column formats, and chromatographic conditions that maximize resolving power and minimize analysis time. In on-line two-dimensional liquid chromatography, dilution-related issues play also an important role and these should be taken into account when developing optimization strategies. In this work, state-of-the-art strategies that support method development for on-line two-dimensional liquid chromatography through a rigorous choice of chromatographic parameters are critically reviewed. The final aim is to provide practitioners with a clear understanding of which aspects can be optimized using current on-line two-dimensional liquid chromatography strategies (and which ones cannot). In two-dimensional liquid chromatography, maximizing resolving power for a given analysis time and dilution requires optimizing efficiency, selectivity and retention. While great strides forward have been made in the optimization of efficiency-related issues, considerable effort needs still to be made in terms of (1) developing models that can predict the retention factors that given stationary/mobile phase systems can provide and (2) using this information for choosing the two ones that maximize two-dimensional liquid chromatography orthogonality. Because of this limitation, in two-dimensional liquid chromatography, this aspect is typically dealt with a posteriori through examining chromatograms. This review clearly shows that important progress in the optimization of on-line two-dimensional liquid chromatography has recently been made.     

单次空时域并行欠采样下的频率和到达角联合估计

随着应用频段的不断升高,空时域欠采样下的入射信号的频率和到达角的联合估计变得愈加困难.为解决此难题,本文提出了一种基于互素稀疏阵列的联合估计器.首先,结合互素稀疏阵列和闭式中国余数定理,建立了频率估计和到达角估计的理论模型;其次,将频谱校正理论和中国余数定理结合起来,导出了频率估计算法;再次,将相位差校正和中国余数定理结合起来,导出了到达角估计算法.该估计器不仅可降低现有估计器的硬件成本,而且仅需对单次并行采样的快拍做并行处理即可获得联合估计结果,无需对单阵元做多次采样,数据处理效率较高.仿真实验表明,该估计器具有较高的鲁棒性估计精度,因而在雷达、遥感等被动感知领域具有较广阔的应用前景.     

On Generalized Schürmann Entropy Estimators

We present a new class of estimators of Shannon entropy for severely undersampled discrete distributions. It is based on a generalization of an estimator proposed by T. Schürmann, which itself is a generalization of an estimator proposed by myself.For a special set of parameters, they are completely free of bias and have a finite variance, something which is widely believed to be impossible. We present also detailed numerical tests, where we compare them with other recent estimators and with exact results, and point out a clash with Bayesian estimators for mutual information.     

CS-MRI 中评价随机欠采样矩阵的新方法

在压缩感知-磁共振成像(CS-MRI)中,随机欠采样矩阵与重建图像质量密切相关．而选取随机欠采样矩阵一般是通过计算点扩散函数(PSF),以可能产生的伪影的最大值为评价参数,评估欠采样对图像重建的影响,然而最大值只反应了伪影的最坏情况．该文引入了两种新的统计学评价参数平均值(MV)和标准差(SD),其中平均值评估了伪影的平均大小,标准差可以反映伪影的波动情况．该文分别使用这3种参数对小鼠和人体脑部MRI数据以不同的采样比率进行CS图像重建,实验结果表明,当采样比率不低于4倍稀疏度时,使用平均值获得了质量更优的重建图像．因此,通过稀疏度先验知识指导合理选取采样比率,并以平均值为评价参数选取随机欠采样矩阵,能够获得更优的CS-MRI重建图像．
     

欠采样包裹相位图的恢复方法

针对非球面光学元件面形检测中的欠采样问题,提出了一种欠采样包裹相位图的恢复方法.首先,将原始欠采样包裹相位图在水平和竖直两个方向进行一个像素的错位相减,得到两个包裹相位差图.其次,对这两个包裹相位差图进行解包裹运算,得到两个解包裹相位差图.最后,应用傅里叶变换和最小二乘法恢复出连续的相位分布.模拟结果表明该方法可以高精...     

Visually weighted reconstruction of compressive sensing MRI

Compressive sensing (CS) enables the reconstruction of a magnetic resonance (MR) image from undersampled data in k-space with relatively low-quality distortion when compared to the original image. In addition, CS allows the scan time to be significantly reduced. Along with a reduction in the computational overhead, we investigate an effective way to improve visual quality through the use of a weighted optimization algorithm for reconstruction after variable density random undersampling in the phase encoding direction over k-space. In contrast to conventional magnetic resonance imaging (MRI) reconstruction methods, the visual weight, in particular, the region of interest (ROI), is investigated here for quality improvement. In addition, we employ a wavelet transform to analyze the reconstructed image in the space domain and fully utilize data sparsity over the spatial and frequency domains. The visual weight is constructed by reflecting the perceptual characteristics of the human visual system (HVS), and then applied to ?₁ norm minimization, which gives priority to each coefficient during the reconstruction process. Using objective quality assessment metrics, it was found that an image reconstructed using the visual weight has higher local and global quality than those processed by conventional methods.