Layer-based decomposition of solids and its applications

In this work we describe a decomposition scheme for polyhedra called layer-based decomposition. This decomposition can be computed in a straightforward way for any kind of polyhedron: convex or nonconvex, genus 0 or higher, etc. and presents interesting properties and applications like point-in-polyhedron inclusion test, computation of Boolean operations, or 3D location. Two methods for computing this decomposition and several of its applications are described in detail, including experimental results and comparisons with alternative approaches.     

A new hierarchical triangle-based point-in-polygon data structure

The point-in-polygon or containment test is fundamental in computational geometry and is applied intensively in geographical information systems. When this test is repeated several times with the same polygon a data structure is necessary in order to reduce the linear time needed to obtain an inclusion result. In the literature different approaches, like grids or quadtrees, have been proposed for reducing the complexity of these algorithms. We propose a new data structure based on hierarchical subdivisions by means of tri-cones, which reduces the time necessary for this inclusion test. This data structure, named tri-tree, decomposes the whole space by means of tri-cones and classifies the edges of the polygon. For the inclusion test only the edges classified in one tri-cone are considered. The tri-tree has a set of properties which makes it specially suited to this aim, with a similar complexity to other data structures, but well suited to polygons which represent regions. We include a theoretical and practical study in which the new data structure is compared with classical ones, showing a significant improvement.     

The empirical optimal envelope and its application to local mean decomposition

Envelopes, which represent the overall information of the signal amplitude variation, are the necessary mediums in many signal decomposition methods. The phenomena of undershoot and overshoot result in the error of envelope estimation and unexpected signal decomposition components. In this paper, an accurate envelope estimation method, called the empirical optimal envelope (EOE), is proposed and applied to the local mean decomposition (LMD). First, an indicator of envelope distance is defined to describe the features of the ideal envelope. Utilizing the indicator, an iterative algorithm for the approximation of tangency points is designed. The tangency points, instead of the extreme points, are interpolated to realize the EOE. Then, the EOE is integrated with the LMD, and two interpolation functions, the cubic spline and the piecewise cubic Hermite interpolating polynomial, are combined to improve the efficiency and convergence of signal decomposition. Finally, the proposed method is verified by simulated signals and actual signals.     

Feature extraction and volume decomposition for orthogonal layered manufacturing

Robust and efficient process planning techniques play an important role in CAD/CAM integration. These techniques need to be developed for each type of manufacturing processes owing to the unique characteristics of each of these processes. In this paper, we describe feature extraction techniques that can be applied to layered manufacturing (LM). The aim is to improve the LM process efficiency by considering the specific feature information of the model, which is normally neglected by previous researches. A feature-based LM system has been developed using these techniques. Based on the proposed orthogonal LM system, features extracted from the geometric analysis are defined in the LM domain, and the algorithm for process planning and volume decomposition based on the specific LM features is proposed and implemented.     

Efficient decomposition methods of fuzzy relation and their application to image decomposition

Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.     

Subspace decomposition approach of fault deviations and its application to fault reconstruction

In the present work, a new subspace decomposition approach of fault deviations is developed in the context of principal component analysis (PCA) based monitoring system for fault diagnosis via reconstruction. The fault effects are decomposed in different monitoring subspaces, principal subspace (PCS) and residual subspace (RS), and the significant fault deviations that are responsible for the concerned alarming monitoring statistic are calculated. This is achieved by designing a two-step feature decomposition procedure in each monitoring subspace. In the first step, the relative fault deviations are sorted by comparing the fault variations with the normal variations. All possible fault deviations that may contribute to the out-of-control monitoring statistics are collected. In the second step, PCA is performed on the chosen fault information where the largest fault deviation directions are decomposed in order. By the two-step decomposition, in each monitoring subspace, two different parts are separated for the purpose of fault reconstruction. One is composed of the concerned fault deviations that contribute to alarming monitoring statistics which are thus significant to remove the out-of-control signals. The other is composed of general variations that are deemed to follow normal rules and thus insignificant to remove alarming monitoring statistics. Theoretical support is framed and the related statistical characteristics are analyzed. Its feasibility and performance are illustrated with data from the three-tank system and the Tennessee Eastman (TE) benchmark process.     

MP稀疏分解快速算法及其在语音识别中的应用

提出一种新的基于Matching Pursuit（MP）的语音信号稀疏分解算法。在对语音信号稀疏分解中使用的过完备原子库进行划分的基础上,将内积运算转换成互相关运算,并结合语音信号与原子是实的特性,利用Fast Hartley Transform（FHT）快速实现互相关运算。从而比利用FFT实现基于MP的信号稀疏分解节省一半的存储空间,提高分解速度约24.8%。此外,应用改进后的算法对语音信号进行特征提取,并结合语音信号的美尔（Mel）频率倒谱参数一起作为该信号的特征向量,通过Support Vector Machine（SVM）进行识别,最后通过实验验证了方法的有效性。     

FOA-LM算法及其在语音信号稀疏分解中的应用

信号的稀疏表示在信号处理的许多方面有着重要的应用,但稀疏分解计算量十分巨大,难以产业化应用。粒子群优化（PSO）及果蝇优化（FOA）等智能算法具备前期收敛速度快,全局搜索能力强的优点,应用到语音信号的稀疏分解中,虽然大大提高了语音信号稀疏分解的速度,但是该类算法后期的收敛速度较低,稀疏分解速度仍然偏低。拉凡格氏（LM）算法具有收敛速度快,精度高的特点,但是LM算法依赖初值,这使它的应用受到了限制。结合智能算法FOA及LM算法的优点,采用FOA算法求出Gabor原子参数初值,利用这些初值进行LM迭代搜索最优原子。仿真结果表明,基于FOA优化算法和LM算法相结合的方法,具有收敛速度快,精度高的特点,有较高的实用价值。     

调速泵结构配置协调分解优化算法及实现

建立多级调速泵结构配置连续非线性规划和整数非线性规划二阶段模型.非线性整数规划子问题采用外逼近算法求解.针对连续非线性规划主问题,提出基于割角法的可行域协调分解优化算法,证明割角法陷阱问题并建立判断准则排除已知的陷阱区域,在此基础上构建系列松弛问题得到原优化问题渐进收紧的下界估计,并最终收敛到原优化问题全局最优解.三级调速泵结构配置实例验证了算法的有效性,并给出与其他算法的比较结果.     

Document representation and its application to page decomposition

Transforming a paper document to its electronic version in a form suitable for efficient storage, retrieval, and interpretation continues to be a challenging problem. An efficient representation scheme for document images is necessary to solve this problem. Document representation involves techniques of thresholding, skew detection, geometric layout analysis, and logical layout analysis. The derived representation can then be used in document storage and retrieval. Page segmentation is an important stage in representing document images obtained by scanning journal pages. The performance of a document understanding system greatly depends on the correctness of page segmentation and labeling of different regions such as text, tables, images, drawings, and rulers. We use the traditional bottom-up approach based on the connected component extraction to efficiently implement page segmentation and region identification. A new document model which preserves top-down generation information is proposed based on which a document is logically represented for interactive editing, storage, retrieval, transfer, and logical analysis. Our algorithm has a high accuracy and takes approximately 1.4 seconds on a SGI Indy workstation for model creation, including orientation estimation, segmentation, and labeling (text, table, image, drawing, and ruler) for a 2550×3300 image of a typical journal page scanned at 300 dpi. This method is applicable to documents from various technical journals and can accommodate moderate amounts of skew and noise     

Further decomposition for singular systems and its properties on geometric subspace

This paper focuses on the relationship between the geometric subspaces and the structural decomposition of continuous-time singular systems. The original structural decomposition is not capable of revealing explicitly the invariant geometric subspaces for singular systems. As such, a further decomposition is necessary and is thus investigated in this paper. Under a new decomposition proposed, the supremal output-nulling (A,E, ImB)-invariant subspace of singular systems can be clearly expressed in an explicit form, and some of its applications are also addressed.     

基于QR分解的RLS算法及在扩频系统的应用研究

相对于扩频系统抑制窄带干扰的时域经典自适应滤波算法,基于QR分解的窄带干扰抑制方法是一种性能优良的新算法.研究了基于QR分解的RLS自适应滤波算法,考虑两种指数加权递归最小二乘(RLS)估计的算法--QR-RLS算法和逆QR-RLS算法,对扩频通信系统进行窄带干扰抑制.通过定义新的数据矩阵,该算法求解出数据域正规方程中的系数矩阵和右侧向量,从而提高了计算效率.最后用Matlab仿真了自适应滤波过程,仿真结果表明,该算法具有良好的计算性能以及收敛性能.     

图像活跃度在图像分解中的应用

在综合分析当前图像压缩算法的基础上,提出新的基于分层变块大小分解的图像压缩构想。JPEG、JPEG2000、分形作为当前最为流行的3种静态图像压缩算法,在对不同的图像进行相同倍率的压缩时,表现出同样的性能趋势：视觉上越复杂的图像,恢复图像的质量越低。经过大量实验发现,3种算法的压缩性能均与同一个指标存在明确关系——图像活跃度量(IAM)。根据图像不同区域的复杂程度不同,采用IAM和相似度作为性能指标,利用粒子群优化(PSO)算法求解最优近似图像,实现对图像的分层变块大小分解（SVBD）,将图像中相同复杂特性的区块归为一类。该分解方式符合人类认知图像内容的特点,为提高压缩性能创造了有利条件。     

The non-overlapping domain decomposition multiplicative schwarz method

Once a decomposition of the finite element space V into two or more subspaces is given, e.g., via domain decomposition, a specific Multiplicative Schwarz Method (MSM) and Additive Schwarz Method (ASM) is defined. In this paper, we analyse the MSM for the decomposition induced by the approximate discrete harmonic finite element basis which was introduced in a joint paper of the authors with A. Meyer (1990). The main theorem of the present paper states that a special symmetric version of the MSM with approximate orthoprojections is equivalent to some ASM with specially chosen basic transformation and block preconditioners. From this observation we can benefit twice. Indeed, the MSM-DD-preconditioner can be analysed in the MSM framework and implemented as specific ASM-DD-preconditioner in the parallel PCG method studied previously. Emphasis that we look at the ASM and MSM as techniques for defining and analysing parallel DD preconditioners used then in a parallelized version of the PCG-method which is well suited for computations on MIMD computers with local memory and message passing principle.     

Advanced control using decomposition and simple elements

The paper explores the standard advanced control elements commonly used in industry for designing advanced control systems. These elements include cascade, ratio, feedforward, decoupling, selectors, split range, and more, collectively referred to as “advanced regulatory control” (ARC). Numerous examples are provided, with a particular focus on process control. The paper emphasizes the shortcomings of model-based optimization methods, such as model predictive control (MPC), and challenges the view that MPC can solve all control problems, while ARC solutions are outdated, ad-hoc and difficult to understand. On the contrary, decomposing the control systems into simple ARC elements is very powerful and allows for designing control systems for complex processes with only limited information. With the knowledge of the control elements presented in the paper, readers should be able to understand most industrial ARC solutions and propose alternatives and improvements. Furthermore, the paper calls for the academic community to enhance the teaching of ARC methods and prioritize research efforts in developing theory and improving design method.     

超方体Qn的路分解及其算法

在超方体[Qn]的路分解的研究中,证明了[Qn]存在[{Pn+1}]-分解的定理;分别给出了[Qn]存在[{P4}]-分解的充分必要条件和存在[{P3,P4}]-分解的充分条件;结合超方体的性质和路分解结论,设计出超方体的路分解算法程序。     

Applying graphics hardware to achieve extremely fast geometric pattern matching in two and three dimensional transformation space

We present a GPU-based approach to geometric pattern matching. We reduce this problem to finding the depth (maximally covered point) of an arrangement of polytopes in transformation space and describe hardware assisted (GPU) algorithms which exploit the available set of graphics operations to perform a fast rasterized depth computation. We give two alternatives, one is for translation + scale and the other is for rigid transformations, both have 3-parameters transformation space. We give extensive experimental results showing the running time of our method and its dependence on various parameters.