Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.     

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.     

Methods for constructing analytic phase function for small spherical particle polydispersions

Two ways of constructing analytic phase function for a polydispersion of small spherical non-absorbing particles have been investigated. First one is a straightforward procedure emanating from the implementation of single particle scattering input into the defined polydisperse phase function. This results in an analytic phase function in terms of moments of the distribution. The second approach is a new strategy, based on the Lagrange mean value theorem. A clear understanding of the relationship between these two approaches has been developed. The efficacy and accuracy of the scattering phase functions is illustrated by applying it to a power-law size distributed sphere ensemble.     

Möbius变换下四次有理抛物-PH曲线的C2 Hermite插值

目的 曲线插值问题在机器人设计、机械工业、航天工业等诸多现代工业领域都有广泛的应用，而已知端点数据的Hermite插值是计算机辅助几何设计中一种常用的曲线构造方法，本文讨论了一种偶数次有理等距曲线，即四次抛物-PH曲线的C² Hermite插值问题。方法 基于M bius变换引入参数，利用复分析的方法构造了四次有理抛物-PH曲线的C² Hermite插值，给出了具体插值算法及相应的Bézier曲线表示和控制顶点的表达式。结果 通过给出"合理"的端点插值数据，以数值实例表明了该算法的有效性，所得12条插值曲线中，结合最小绝对旋转数和弹性弯曲能量最小化两种准则给出了判定满足插值条件最优曲线的选择方法，并以具体实例说明了与其他插值方法的对比分析结果。结论 本文构造了M bius变换下的四次有理抛物-PH曲线的C² Hermite插值，在保证曲线次数较低的情况下，达到了连续性更高的插值条件，计算更为简单，插值效果明显，较之传统奇数次PH曲线具有更加自然的几何形状，对偶数次PH曲线的相关研究具有一定意义。     

基于克里金理论的辐射剂量场插值重构与可视化研究

使用基于克里金理论的插值计算方法对均匀网格与随机排列等不同分布类型的辐射剂量场进行了数据重构与可视化研究,并将重构结果与常用的反距离加权插值法进行了对比,分析了不同插值方法对辐射剂量场重构精度与可视化显示效果的影响。结果表明:对于多数情况,克里金插值法在辐射剂量场重构的精度与可视化显示的效果上均明显优于反距离加权插值法,算例中克里金插值法的结果与原始数据之间的偏差在10%以内,而反距离加权插值法的结果与原始数据之间的偏差基本在15%以上;但在辐射剂量场梯度变化较大且已知数据极少的区域,克里金插值法的计算结果偏差会增大,此时可使用反距离加权插值作为其补充,综合使用。本文的研究工作,验证了克里金插值法在辐射剂量场重构与可视化方面的应用潜力,可为推动辐射剂量场可视化仿真技术的发展提供技术支持。     

Improved error bound for multivariate Chebyshev polynomial interpolation

ABSTRACT

Chebyshev interpolation is a highly effective, intensively studied method and enjoys excellent numerical properties which provides tremendous application potential in mathematical finance. The interpolation nodes are known beforehand, implementation is straightforward and the method is numerically stable. For efficiency, a sharp error bound is essential, in particular for high-dimensional applications. For tensorized Chebyshev interpolation, we present an error bound that improves existing results significantly.     

基于多尺度结构特征的快速异源图像匹配

针对异源图像提出一种基于多尺度密集结构特征的快速匹配算法。算法首先利用Gabor滤波器逐像素提取图像中的结构响应,再根据主方向响应对多尺度结构特征融合,然后使用快速傅里叶变换在频域计算各特征分量图像之间的卷积,最后将卷积生成的系数矩阵求和计算出图像之间的相似性并选择相似性最大位置作为匹配结果输出。本文算法能有效适应异源图像间的非线性灰度变化和噪声干扰问题。测试使用可见光、红外、雷达图像组成的异源图像数据集对本文算法和现有算法进行测试比较,结果表明:本文算法的平均误匹配率最低,并且计算速度有明显优势。     

基于一种改进逐点比较插补法的激光打标机控制加工算法

在激光打标系统中,逐点比较插补法是一种普遍使用的算法。这种算法在控制激光运动轨迹和对图像轨迹的拟合过程中,起到极其重要的作用。由于逐点比较插补法具有运算直观,脉冲输出均匀,调节方便等特点,所以是一种较为适合打标机系统应用的插补算法。但是传统的逐点比较插补算法存在精度低和速度慢等问题。为了改善该算法的性能,对传统逐点比较插补算法进行了改进,并进行了计算和模拟仿真。结果表明改进比较插补算法在精度和速度上都有明显提高。