有理多结点样条插值曲线及曲面

鉴于多结点样条曲线（MSIC）是一种点点通过的插值样条曲线,因此在多结点样条插值曲线研究的基础上,给出了有理多结点条插值曲线和有理多结点样条插值曲面的定义,并讨论了有理多结点样条的性质,对有理多结 样条曲线和有理多结点样条曲面的光滑拼接问题进行了讨论,此外,还对有理多结点样条在计算机辅助几何设计中的若干应用问题进行了说明。     

多结点样条插值及其多尺度细化算法

针对风线与曲面拟事问题，研究多结点样条插值方法。这类方法具有基数型，显式计算及局部性等优点。主要的新结果是：对多结点样条基本函数的构造给出了新的表述；提出了一类新的不带移动的混合形多结点样条基本函数；基于多尺度分析的思想，给出了一种自适应的细化算法，它对消减采样数据的相关性是简便有效的。     

Single-knot wavelets for non-uniform B-splines

We propose a flexible and efficient wavelet construction for non-uniform B-spline curves and surfaces. The method allows to remove knots in arbitrary order minimizing the displacement of control points when a knot is re-inserted. Geometric detail subtracted from a shape by knot removal is represented by an associated wavelet coefficient replacing one of the control points at a coarser level of detail. From the hierarchy of wavelet coefficients, perfect reconstruction of the original shape is obtained. Both knot removal and insertion have local impact. Wavelet synthesis and analysis are both computed in linear time, based on the lifting scheme for biorthogonal wavelets. The method is perfectly suited for multiresolution surface editing, progressive transmission, and compression of spline curves and surfaces.     

Identification of IIR Wiener systems with spline nonlinearities that have variable knots

An algorithm is developed for the identification of Wiener systems, linear dynamic elements followed by static nonlinearities. In this case, the linear element is modeled using a recursive digital filter, while the static nonlinearity is represented by a spline of arbitrary but fixed degree. The primary contribution in this note is the use of variable knot splines, which allow for the use of splines with relatively few knot points, in the context of Wiener system identification. The model output is shown to be nonlinear in the filter parameters and in the knot points, but linear in the remaining spline parameters. Thus, a separable least squares algorithm is used to estimate the model parameters. Monte-Carlo simulations are used to compare the performance of the algorithm identifying models with linear and cubic spline nonlinearities, with a similar technique using polynomial nonlinearities.     

Data based segmentation and summarization for sensor data in semiconductor manufacturing

In semiconductor manufacturing processes, sensor data are segmented and summarized in order to reduce storage space. This is conventionally done by segmenting the data based on predefined chamber step information and calculating statistics within the segments. However, segmentation via chamber steps often do not coincide with actual change points in data, which results in suboptimal summarization. This paper proposes a novel framework using abnormal difference and free knot spline with knot removal, to detect actual data change points and summarize on them. Preliminary experiments demonstrate that the proposed algorithm handles arbitrarily shaped data in a robust fashion and shows better performance than chamber step based segmentation and summarization. An evaluation metric based on linearity and parsimony is also proposed.     

Free knot splines for logistic models and threshold selection

The logistic regression model has been in use in statistical analysis for many years. The paper introduces a spline model to remove the linear restriction on logit function. By considering knot locations as free variables, spline approximation of data is improved. The number of knots and the degree of the spline functions can still be determined by using a model selection procedure. Moreover, a knot, seen as a free parameter for a piecewise linear spline, represents a break point in the logit function which may be interpreted as a threshold value. This method is applied to a clinical trial for an in vitro fertilization program.     

Knot calculation for spline fitting via sparse optimization

Curve fitting with splines is a fundamental problem in computer-aided design and engineering. However, how to choose the number of knots and how to place the knots in spline fitting remain a difficult issue. This paper presents a framework for computing knots (including the number and positions) in curve fitting based on a sparse optimization model. The framework consists of two steps: first, from a dense initial knot vector, a set of active knots is selected at which certain order derivative of the spline is discontinuous by solving a sparse optimization problem; second, we further remove redundant knots and adjust the positions of active knots to obtain the final knot vector. Our experiments show that the approximation spline curve obtained by our approach has less number of knots compared to existing methods. Particularly, when the data points are sampled dense enough from a spline, our algorithm can recover the ground truth knot vector and reproduce the spline.     

Approximation and estimation bounds for free knot splines

The fitting to data by splines has long been known to improve dramatically if the knots can be adjusted adaptively. To demonstrate the quality of the obtained free knot spline, it is essential to characterize its generalization ability. By utilizing the powerful techniques of the empirical process and approximation theory to address the estimation and approximation error bounds, respectively, the generalization ability of the free knot spline learning strategy is successfully characterized. We show that the Pseudo-dimension of free knot splines is essentially a linear function of the number of knots. A class of rather general loss functions is considered here and the squared loss is specially treated for its excellent property. We also provide some numerical results to demonstrate the utility of these theoretical results in guiding the process of choosing the appropriate knot numbers through the training data to avoid the overfitting/underfitting problem.     

Wavelet-Based Data Reduction of B-Spline Curves

1 Introduction The problem of reducing the amount of data in the representation of a function or a curve is not new. Many papers have already been published. In these strategies, two trends can be emphasized[1]. The first one deals with polygonal curves for approximating data[2],[3]. Another approach is based on spline curves[4]~[8]. In the first approach, the problem is formulated so that the perpendicular distance of each point on the curve to the fitted line segments is within a predefined…     

Surface reconstruction using bivariate simplex splines on Delaunay configurations

Recently, a new bivariate simplex spline scheme based on Delaunay configuration has been introduced into the geometric computing community, and it defines a complete spline space that retains many attractive theoretic and computational properties. In this paper, we develop a novel shape modeling framework to reconstruct a closed surface of arbitrary topology based on this new spline scheme. Our framework takes a triangulated set of points, and by solving a linear least-square problem and iteratively refining parameter domains with newly added knots, we can finally obtain a continuous spline surface satisfying the requirement of a user-specified error tolerance. Unlike existing surface reconstruction methods based on triangular B-splines (or DMS splines), in which auxiliary knots must be explicitly added in advance to form a knot sequence for construction of each basis function, our new algorithm completely avoids this less-intuitive and labor-intensive knot generating procedure. We demonstrate the efficacy and effectiveness of our algorithm on real-world, scattered datasets for shape representation and computing.     

A simple,efficient degree raising algorithm for B-spline curves

This paper presents a new algorithm to compute the degree-raised version of a spline. The new algorithm is as fast as the best existing algorithm, but is much easier to understand and to implement. The new control vertices of the degree-raised spline are obtained simply by a series of knot insertions followed by a series of knot deletions.     

Shape-preserving knot removal

Starting with a shape-preserving C¹ quadratic spline, we show how knots can be removed to produce a new spline which is within a specified tolerance of the original one, and which has the same shape properties. We give specific algorithms and some numerical examples, and also show how the method can be used to compute approximate best free-knot splines. Finally, we discuss how to handle noisy data, and develop an analogous knot removal algorithm for a monotonicity preserving surface method.     

带参数的多结点样条

多结点样条函数是在通常样条函数中引入更多的附加结点，其优越性表现在使插值过程无须求解任何方程组，而且有局部性，对多结点样条函数做进一步研究，构造了一类带参数的多结点样条基本函数．该类函数不仅保持了一般多结点样条函数的优点，而且由于参数的引进，使得基数型的插值公式可形成一族，可以根据实际问题的需要在函数(曲线)族中作出最优选择．文中研究的带参数的多结点样条函数，除了能用于表达平滑的数据及几何造型之外。尤其能适应波动较大、频率较高的数据拟合问题，有助于解决信号处理及非规则几何造型的一些问题。     

由递归插入——斜移过程实现插入节点算法

Ｂ样条的插入节点算法有广泛的应用，引起了不少学者的兴趣。该文引入了递归插入和斜移过程来实现插入节点算法，概念清晰，算法实现简单，应用方便。这一方法较以前的各种算法速度更快。本文亦给出生成分段Ｂｅｚｉｅｒ点的一个富于特色的算法。     

结点插值新算法

结点插值算法广泛应用开发系统样条曲线、曲面的生成表示和求交分类。本文给出的结点插值新算法不仅可以统一表示已知的Boehm算法和Oslo算法,而且算法效率上优于它们。本算法已用于三维几何造型系统GEMS中。     

数据去冗余的多尺度多结点技术

从多结点样条理论出发，提出一种自适应的多层次淘汰冗余数据的算法，并通过不同的采样数据对算法进行了有效的论证．充分利用多结点样条函数拟合的基数型、显式计算和局部性等优点．该算法可用于采样数据的压缩或针对现有算法的数据预处理．     

B样条曲线曲面GC2扩展

提出了一个扩展B样条曲线曲面的新方法,扩展B样条曲线曲面的关键是为新增加的点确定节点值,新方法的基本思想是：首先,B样条曲线和扩展部分在连接点处满足GC^2连续,用能量极小化方法确定扩展部分的曲线形状,通过对曲线重新参数化使两部分曲线满足C^2连续,进而确定新增加点的节点值,新B样条曲线的控制点由一个显式递推公式计算,原B样条曲线和扩展后的部分合在一起形成一条新的B样条曲线,新的B样条曲线满足原B样条曲线和扩展的点,文章还讨论了运用该方法进行B样条曲面扩展,且以实例对新方法与其它方法进行了比较,结果表明新方法的光顺性得到了明显改善,曲率变化更平坦,且有较小的旋转数指标。     

高精度三次参数样条曲线的构造

构造参数样条曲线的关键是选取节点，该文讨论了GC^2三次参数样条曲线需满足的连续性方程，提出了构造GC^2三次参数样条曲线的新方法，在讨论了平面有序五点确定一组三次多项式函数曲线，平面有序六点唯一确定一条三次多项式函数曲线的基础上，提出了计算相邻两区间上的节点的算法，构造的插值曲线具有三次多项式函数精,该文还以实例对新方法与其它方法构造的插值曲线的精度进行了比较。     

B样条曲线节点插入和升阶的统一方法

利用 B样条基转换矩阵的有关结果 ,本文给出了 B样条曲线插入节点和升阶的统一方法及算法 .本文方法建立在严密的数学背景上 ,以简洁严谨的递推公式给出其算法的数学模型 ,相应的算法效率高且易实现 ,算法的时间复杂性为 O((k- k 1) kn) ,其中 k,k分别为升阶前后曲线的阶 ,n k 1为插入节点和升阶后的节点数 .而且 ,本文方法及算法使用灵活 ,适用范围广 ,可用于同时插入任意个相同的或不同的节点并升任意阶 ,也可用于只插入节点或只升阶 .Cohen等的 Oslo算法、升阶方法都是本文方法的特例 ,而且本文方法效率更高     

一种B样条表面插值控制点的缩减方法

研究了从给定节点向量中选择节点进行B样条曲线插值的方法，并将此方法应用到行数据点不相同的B样条曲面插值，得到了一个通过对行节点矢量调整传递的曲面插值方法，理论分析和实验表明该方法可大量减少曲面控制点的数目．