超声逆散射成像问题中的截断完全最小二乘法

在超声逆散射成像问题中,由于要反复迭代求物体内部的全场与未知函数,使得方程组的系数矩阵与数据项均存在误差,将同时考虑系数矩阵和数据项均存在误差的截断完全最小二乘正则化方法运用于超声逆散射成像问题中．数值仿真结果显示,截断完全最小二乘法与传统的Tikhanov的正则化方法相比,可以提高数据的拟合程度,也即提高了成像的质量．     

Low-Complexity Bit-Parallel Multiplier over GF(2$^m$) Using Dual Basis Representation

Recently, cryptographic applications based on finite fields have attracted much attention. The most demanding finite field arithmetic operation is multiplication. This investigation proposes a new multiplication algorithm over GF（2^m） using the dual basis representation. Based on the proposed algorithm, a parallel-in parallel-out systolic multiplier is presented, The architecture is optimized in order to minimize the silicon covered area （transistor count）. The experimental results reveal that the proposed bit-parallel multiplier saves about 65% space complexity and 33% time complexity as compared to the traditional multipliers for a general polynomial and dual basis of GF（2^m）.     

Research of assembling optimized classification algorithm by neural network based on Ordinary Least Squares (OLS)

A new optimized classification algorithm assembled by neural network based on Ordinary Least Squares (OLS) is established here. While recognizing complex high-dimensional data by neural network, the design of network is a challenge. Besides, single network model can hardly get satisfying recognition accuracy. Firstly, feature dimension reduction is carried on so that the design of network is more convenient. Take Elman neural network algorithm based on PCA as sub-classifier I. The recognition precision of this classifier is relatively high, but the convergence rate is not satisfying. Take RBF neural network algorithm based on factor analysis as sub-classifier II. The convergence rate of the classifier algorithm is fast, but the recognition precision is relatively low. In order to make up for the deficiency, by carrying on ensemble learning of the two sub-classifiers and determining optimal weights of each sub-classifier by OLS principle, assembled optimized classification algorithm is obtained, so to some extent, information loss caused by dimensionality reduction in data is made up. In the end, validation of the model can be tested by case analysis.     

运用Chi2算法的一种变形简化决策树归纳的实例表示空间

决策树归纳的两个重要阶段是数据表示空间的简化和决策树的生成。在将训练集的不一致率控制在某一阈值的前提下,减少实例的属性个数和各个属性的取值个数保证了决策树方法的可行性和有效性。本文在Chi2算法的基础上运用它的一种变形进行属性取值离散化和属性筛选,然后运用算术运算符合并取值个数为2或3的相邻属性。在此基础上生
成的决策树具有良好的准确性。实验数据采用的是一个保险公司捐献的数据集。     

A Deterministic Construction of Normal Bases With Complexity O(n3 + n log n log(log n) log q)

Constructing normal bases of GF(qⁿ) over GF (q) can be done by probabilistic methods as well as deterministic ones. In the following paper we consider only deterministic constructions. As far as we know, the best complexity for probabilistic algorithms is O(n² log⁴n log² (log n) + n log n log (log n) log q ) (see von zur Gathen and Shoup, 1992). For deterministic constructions, some prior ones, e.g. Lueneburg (1986), do not use the factorization of Xⁿ - 1 over GF(q). As analysed by Bach, Driscoll and Shallit (1993), the best complexity (from Lueneburg, 1986) is O(n³ log n log(log n) + n² log n log(log n) log q). For other deterministic constructions, which need such a factorization, the best complexities are O(n^3,376 + n² log n log(log n) log q) (von zur Gathen and Giesbrecht, 1990), or O(n³ log q); see Augot and Camion (1993). Here we propose a new deterministic construction that does not require the factorization of Xⁿ - 1. Its complexity is reduced to O (n³ + n log n log(log n) log q ).     

一个常微分方程的整体解存在性

该文研究了常微分方程(d2u/dx2)+K(x)2n=0在(-1,1)上整体解的存在性,此问题源于H2上的预定保角高斯曲率问题,证明了一个存在定理,解释了其几何意义.     

基于轨迹系数特征空间表示法的含有异常情况的自动运动学习

Techniques for understanding video object motion activity are becoming increasingly important with the widespread adoption of CCTV surveillance systems. Motion trajectories provide rich spatiotemporal information about an object's activity. This paper presents a novel technique for clustering of object trajectory-based video motion clips using basis function approximations. Motion cues can be extracted using a tracking algorithm on video streams from video cameras. In the proposed system, trajectories are treated as time series and modelled using orthogonal basis function representation. Various function approximations have been compared including least squares polynomial, Chebyshev polynomials, piecewise aggregate approximation, discrete Fourier transform (DFT), and modified DFT (DFT-MOD). A novel framework, namely iterative hierarchical semi-agglomerative clustering using learning vector quantization (Iterative HSACT-LVQ), is proposed for learning of patterns in the presence of significant number of anomalies in training data. In this context, anomalies are defined as atypical behavior patterns that are not represented by sufficient samples in training data and are infrequently occurring or unusual. The proposed algorithm does not require any prior knowledge about the number of patterns hidden in unclassified dataset. Experiments using complex real-life trajectory datasets demonstrate the superiority of our proposed Iterative HSACT-LVQ-based motion learning technique compared to other recent approaches.     

二维空间中硬聚类算法影响力因子的作用研究

经典硬聚类算法HCM(hardc-means)完全基于欧氏距离,针对其无法较好应对各簇规模差异较大的情况,提出在每个欧氏距离项上加入一个影响力因子,使基于距离的标准转变为更通用的基于角度的标准的方法(HCMef算法)。用该算法对二维空间中两类分布密度基本一致,样本数对比分别为1000∶1000、1000∶5000和1000∶10000,正态分布且类边界从较模糊到较清晰的不同数据进行试验。结果显示,HCMef方法可以很好地找到聚类中心的标准设定值,在各种情况下都有很明显优势,表现出很强的稳定性。表明该方法在二维两类情况下的可行性,并值得做进一步推广研究。     

杂合型全局优化法优化Sr2+(H2O)n团簇

以半经验的势能函数描述H_2O-H_2O之间和Sr~(2 )-H_2O间的相互作用,采用杂合型全局优化法(fast hybrid global optimiza- tion algorithm,FHGOA)搜索Sr~(2 )(H_2O)_n(n=1-30)团簇的最优结构。结果表明：当n=1-8时,团簇为n_1 0结构,其中,在n_1=5-7时,优化出的团簇结构与实验结果相吻合;当n=9-19时,团簇结构为8 n_2结构;当n=20-30,团簇结构为9 n_2结构。根据实验结果推断：在Sr~(2 )水溶液中,Sr~(2 )的水化数为9,此结果和MC模拟的结果是一致的。     

(n+1)维空间Cn[a,b]上规范B基存在的充要条件

给出(n 1)维空间C^n[a,b]上规范B基存在的充要条件，并就摆线的规范B基的非退化表示进行讨论，得到了函数空间Pl＝span{l，t，cost,sint}中摆线的非退化规范B基表示．     

(X+K)mod2n和X(+)K相容程度分析

"与K模2n加"-Y=(X+K)mod2n是密码算法中一个常用的基本编码环节,这里的K表示一个固定的常数.该环节具有较好的非线性性质,在许多分组密码、流密码算法以及杂凑函数中都有着广泛的应用.研究了(X+K)mod2n和X(+)K的相容程度,给出了噪声函数N(x)=(X+K)mod2nX(+)K在各点概率的计算公式以及在各点概率值平方和的一些性质.     

基于频域最小距离的SPOT(Pan)图像纹理分类算法

为了将频谱对纹理特性的表征能力应用于遥感图像分类提出了基于频域最小距离遥感图像纹理分类算法。将模板图像和适当窗口大小的待判别图像分别进行傅立叶变换,计算两者的频域距离,距离最小者即判别窗口中心像元为该类别的地物。运用该方法对SPOT(Pan)图像进行纹理分类试验,结果表明窗口大小为3×3时分类效果最好,总体分类精度达到80.4%。     

An O(k~2n~2) Algorithm to Find a k-Partition in a k-Connected Graph

Although there are polynomial algorithms of finding a 2-partition or a 3-partition for a simple undirected 2-connected or 3-connected graph respectively,there is no general algorithm of finding a k-partition for a k-connected graph G=(V,E),where k is the vertex connectivity of G.In this paper,an O(k^2n^2) general algorithm of finding a k-partition for a k-connected graph is proposed,where n=|V|.     

2-D Roesser模型的静态干扰解耦

本文讨论了2-D Roesser模型[1](RM)的静态干扰解耦问题[2](简称为2-D DDP),即寻求2-D状态反馈使相应的闭环系统具有抗干扰的能力,得到了问题有解的充分条件和计算相应反馈阵的算法.     

A method for exact reliability of consecutive2-out-of-(r, r)-from-(n, n):F systems

A new reliability model, consecutive 2‐out‐of‐(r, r)‐from‐(n, n):F model, is proposed. The consecutive 2‐out‐of‐(r, r)‐from‐(n, n):F system consists of a square grid of side n (containing n² components) such that the system fails if and only if there is at least one square of side r which includes among them at least two failed components. For i.i.d. case an algorithm is given for computing the reliability of the system. The reliability function can be expressed by the number of 0–1 matrices having no two or more 0s at any square of side r.     

一般2-D线性常系数离散状态空间模型渐近稳定性的一类Lyapunov方法

本文给出了一般2-D线性常系数离散状态空间模型(2-D GM)的渐近稳定性的定义以及相应的判据,并借助于Lyapunov方程给出了2-D Roesser Model(2-D RM)渐近稳定条件,推广和简化了文献[1,7]的有关结论。最后通过行列式的一个简单性质,证明了关于2-DGM渐近稳定性的判定可以转化为一类特殊的2-D RM的相应问题,从而得到了判定2-D GM渐近稳定性的Lyapunov方法。     

Rational Zoom of Bit Maps Using B-Spline Interpdation in Computerized 2-D Animation

This paper describes the application of B-spline interpolation to the problem of rational transformation in computerized 2-D animation. The technique described herewith can also be applied to the resolution independence problem which arises when the same production workstation is used to produce animation series to be recorded on variable film sizes This article fully explains our solution to the problem of rational zoom. An algorithm has been written to speed up computations by spreading the computing load among similar technical workstations hooked up in a network. Large magnifications of professional quality can be achieved in very little time and very smooth animation effects can be obtained by applying rational zooms with magnification coefficients that are a time function.     

New (n, r)-arcs in PG(2, 17), PG(2, 19), and PG(2, 23)

An (n, r)-arc is a set of n points of a projective plane such that some r but no r+1 of them are collinear. The maximum size of an (n, r)-arc in PG(2, q) is denoted by m _r (2, q). In this paper a new (95, 7)-arc, (183, 12)-arc, and (205, 13)-arc in PG(2, 17) are constructed, as well as a (243, 14)-arc and (264, 15)-arc in PG(2, 19). Likewise, good large (n, r)-arcs in PG(2, 23) are constructed and a table with bounds on m _r (2, 23) is presented. In this way many new 3-dimensional Griesmer codes are obtained. The results are obtained by nonexhaustive local computer search.     

AnO(n 2) incremental algorithm for modular decomposition of graphs and 2-structures

This paper gives anO(n ²) incremental algorithm for computing the modular decomposition of 2-structures [1], [2]. A 2-structure is a type of edge-colored graph, and its modular decomposition is also known as the prime tree family. Modular decomposition of 2-structures arises in the study of relational systems. The modular decomposition of undirected graphs and digraphs is a special case, and has applications in a number of combinatorial optimization problems. This algorithm generalizes elements of a previousO(n ²) algorithm of Muller and Spinrad [3] for the decomposition of undirected graphs. However, Muller and Spinrad's algorithm employs a sophisticated data structure that impedes its generalization to digraphs and 2-structures, and limits its practical use. We replace this data structure with a scheme that labels each edge with at most one node, thereby obtaining an algorithm that is both practical and general to 2-structures.     

Ab initio study of mono-layer 2-D insulators (X-(OH)2 and h-BN) and their use in MTJ memory device

The paper presents an ab initio study of the 2-D insulators and their effect on the performance of a magnetic tunnel junction memory (MTJ) device. MTJ devices has been considered as an alternate to the charge based data storage cells due to its spin-polarised operation and high scaling probability. The use of 2-D insulators like X-(OH)₂ (X: Ca and Mg) and h-BN (hexagonal-Boron Nitride) in such device would be interesting. The authors have calculated the band structures, density of states and effective mass of electrons and holes for the mono-layer of these three non-conventional 2-D insulators using the first principle calculations in density functional theory framework using Quantumwise ATK tool. The ab initio calculation yielded band gap (E_g) of 4.633, 4.685 and 4.249 eV for h-BN, Ca(OH)₂ and Mg(OH)₂, respectively. The effective mass of electrons was calculated as 0.621, 0.604 and 0.478 for single layer h-BN, Ca(OH)₂ and Mg(OH)₂, respectively. While for holes it is 0.834, 0.446 and 0.407, respectively for h-BN, Ca(OH)₂ and Mg(OH)₂. The MTJ device properties as tunneling-magneto resistance, differential TMR, parallel and anti-parallel resistance, differential resistance and spin transfer torque components (in-plane and out-of-plane) with these materials as composite dielectric has been reported in this paper using MTJ Lab tool. The performance of MTJ memory device with h-BN based composite dielectric is found better.