基于纹理分析的视差估计算法

针对传统方法难以可靠估计图像中纹理单一像素点视差的问题,提出一种新的基于纹理分析的视差估计算法。与已有方法不同,在以极线约束计算像素点视差时,将极线上纹理单一且近似的像素点合并成直线段,根据连续性和唯一性约束对直线段进行整体匹配,采用直线段的视差得到纹理单一区域的稠密视差图。利用直线段进行整体匹配,提高比较基元包含的信息量,减少扫描范围,从而降低误匹配产生的概率和算法时间复杂度。实验结果表明,该方法能提高纹理单一区域稠密视差图的精度,匹配速度快,具有实用价值。     

A bound for random and closed loop burst error detecting codes

A sufficient condition for a linear code that has a given minimum weight and having no closed loop burst of a specified length or less is derived. The bound derived assures the existence of a code that can detect errors which are either random errors of a given weight and less or closed loop bursts of a specified length or less. An asymptotic form of the bound is also discussed.     

Integer Cosine Transforms for High-Efficiency Image and Video Coding

Matrix methods for constructing one-norm order-8 and -16 integer cosine transforms are considered. One-norm order-8 and -16 integer transforms are proposed and fast algorithms are developed that implement these transforms with a low computational complexity that is less by a factor of 3–5 than the complexity of well-known algorithms and is less by a factor of 10 than that in the H.265 standard.     

The impact of fourth generation languages on systems development

The purpose of this study was to identify the nature and scope of systems development projects in which 4GL's are being used, to compare these projects with projects in which procedural languages are being used, and to describe the benefits and limitations of 4GL's. Project managers with experience managing both traditional and 4GL projects returned questionnaires describing the size, cost, duration, scope and characteristics of these applications. The results indicated that project managers made a clear distinction between the types of projects that are appropriate for development using procedural languages and 4GL's. Procedural projects had higher transactions volumes, cost more, required more person-days, and were generally larger in scale. In contrast, 4GL projects had more variable outputs, less security requirements, less chance of audit, and less complexity. The perfect 4GL project was an inquiry and reporting system with less structured outputs, dynamic scheduling requirements, and low transactions volumes. MIS professionals recognize the benefits and limitations of 4GL's and are generally making good decisions about their use.     

关于盲信号自适应分离中非线性函数的讨论

This paper proposes a new algorithm of blind source separation (BSS). The algorithm can overcome the difficulty known as “the sensors are less than the source signals” and works effectively when the sensors are less. Then, the paper discusses the nonlinear functions used in the new algorithm. A uniform nonlinear function is proposed and some criterion are given to choose its parameters. Finally, some simulations are presented to show the effectness of the algorithm and the correctness of the criterion.     

含离散和分布时变时延神经网络系统的指数稳定性

针对一类含有离散和分布时延神经网络,在神经激活函数较弱的约束条件下,通过定义一个更具一般性的Lyapunov泛函,使用凸组合技术,得到了新的基于线性矩阵不等式表示的指数稳定性判据.与现有结果相比,这些判据具有较小的保守性.仿真算例表明,得到的结果是有效的且保守性小.     

少故障数据条件下SFEP最终事件发生概率分布确定方法

为了在获得少故障数据条件下得到适合的系统故障演化过程（system fault evolution process，SFEP）中最终事件发生概率分布，提出一种考虑信息扩散且数据较少情况下的最终事件发生概率分布计算方法。该方法利用信息扩散原理以事件发生时因素为中心在研究区域内形成正态分布。同一事件的多次发生在研究区域中取最大值形成该事件发生概率分布，从而得到SFEP中边缘事件发生概率分布。将SFN中事件关系表示为关系组从而叠加关系，得到最终事件发生概率分布解析式计算分布。研究表明，所得结果与原有精确结果具有较高的符合性，但所需故障数据则少得多。可借助该方法在少故障数据条件下研究SFEP最终事件发生特征。     

无线传感器网络中分布式存储方案的改进

本文提出了一种效率较高的无线传感器网络的分布式数据存储方案。该方案将数据D加密成n个秘密共享份分别存储于无线传感器网络的n个存储节点中,只有从这n个存储节点中获得有效秘密共享份数大于或等于预先设定的阀值k（1≤k≤n）时才可重构原始数据;而获得任意小于份的共享份数将得不出原始数据。这样,在加密了数据的同时,又能使得WSN在一部分节点失效（失效的节点数小于k）的情况下仍然能获得原始数据,从而提高了数据的可靠性和容灾性。相对于运用Shamir秘密共享方案,本方案将更有效率。     

基于FCM和HVS的密写方法

为了提供较大的秘密信息嵌入量和保持良好的载密图像质量,该文提出一种基于模糊C均值聚类和人眼视觉特性的图像密写。该密写方法将对比度和梯度敏感度作为特征向量,并通过模糊C均值聚类将像素分为视觉敏感类与视觉不敏感类,将较多秘密信息嵌入属于视觉不敏感类的像素,而将较少秘密信息嵌入属于视觉敏感类的像素。实验结果表明,与四边匹配算法相比,该算法有更大的嵌入量并保持了良好的载密图像质量。     

Stochastic exponential stability for Markovian jumping BAM neural networks with time-varying delays.

This correspondence provides stochastic exponential stability for Markovian jumping bidirectional associative memory neural networks with time-varying delays. An approach combining the Lyapunov functional with linear matrix inequality is taken to study the problems. Some criteria for the stochastic exponential stability are derived. The results obtained in this correspondence are less conservative, less restrictive, and more computationally efficient than the ones reported so far in the literature.     

New Delay-Dependent Stability Results for Neural Networks With Time-Varying Delay

This paper studies the problem of stability analysis for neural networks (NNs) with a time-varying delay. Unlike the previous works, the activation functions are assumed to be neither monotonic, nor differentiable, nor bounded. By defining a more general type of Lyapunov functionals, some new less conservative delay-dependent stability criteria are established in terms of linear matrix inequalities (LMIs). Meanwhile, the computational complexity of the newly obtained stability conditions is reduced because less variables are involved. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.     

具有多状态和控制时滞的控制系统的绝对稳定性分析

基于线性矩阵不等式方法, 对具有多个状态和控制的时变时滞的Lurie型控制系统的稳定性进行分析, 得到了系统绝对稳定的几个充分条件, 这些条件用线性矩阵不等式表示, 具有较低的保守性. 最后通过一个实例验证了所得条件的保守性较以往结果的保守性小.     

Stabilization of Takagi–Sugeno Model via Nonparallel Distributed Compensation Law

This paper addresses the stabilization of nonlinear systems, which is represented by a Takagi–Sugeno (T–S) model. Based on the extended nonquadratic Lyapunov function and the nonparallel distributed compensation law, three new results are obtained by using appropriate slack matrices, collection matrices, and the higher dimensional collection matrix. The first two results are less conservative, and computationally less expensive, than some of the existing results. The third result combines the procedures of the first two results, and is less conservative, but is computationally more expensive than the first two results. The effectiveness of the new results is validated by two numerical examples.      

Stability analysis of linear time-varying systems: Improving conditions by adding more information about parameter variation

In this paper a new Lyapunov function is proposed for stability analysis of linear time-varying systems. This new function carries more information regarding parameter variation leading to less conservative conditions. Using Finsler’s lemma and a suitable form to describe the high-order time-derivatives of the parameters, finite sets of LMIs are obtained which are progressively less conservative as a pair of parameters grow. Previous results can be seen as a special case and numerical examples are carried out for the sake of illustration.     

两种常用编码方法的研究及C#实现

图像压缩是数字图像处理的一项重要技术。论文研究了基于统计特性的两种熵编码图像压缩编码方法——香农编码和哈夫曼编码,并以C#为工具,对两种编码方法进行实验及对比。实验表明,哈夫曼编码的编码效率远高于香农编码。香农编码占用的存储空间较大,单位码长表达的信息量少;哈夫曼编码节省存储空间,单位码长表达了更为丰富的信息量。     

Injuries and the 'poor' worker

It is commonly assumed that occupational injuries are less of a problem in developing countries because there is less industrialization. Spot studies reveal, however, that injuries are a serious problem among miners, agricultural workers, and industrial workers in most countries

Each nation differs greatly in its level of industrialization, laws, working conditions, and range of products. Those with lower per capita incomes and lower levels of industrialization are likely to have more decentralized production which is less likely to be controlled effectively. Workers in developing countries are more likely to be injured; injuries are more likely to be disabling; and rehabilitation services more likely to be unavailable. Workers' transiency makes it more difficult for them to appreciate hazards which operate over long periods. Finally, workers' social status and level of organization in many cases greatly reduces their power to promote change

In this paper, an attempt is made to understand which experiences of the rich industrialized nations are valid for other nations and what new research needs to be done.     

Importance-driven feature enhancement in volume visualization

This paper presents importance-driven feature enhancement as a technique for the automatic generation of cut-away and ghosted views out of volumetric data. The presented focus+context approach removes or suppresses less important parts of a scene to reveal more important underlying information. However, less important parts are fully visible in those regions, where important visual information is not lost, i.e., more relevant features are not occluded. Features within the volumetric data are first classified according to a new dimension, denoted as object importance. This property determines which structures should be readily discernible and which structures are less important. Next, for each feature, various representations (levels of sparseness) from a dense to a sparse depiction are defined. Levels of sparseness define a spectrum of optical properties or rendering styles. The resulting image is generated by ray-casting and combining the intersected features proportional to their importance (importance compositing). The paper includes an extended discussion on several possible schemes for levels of sparseness specification. Furthermore, different approaches to importance compositing are treated.     

Complete delay-decomposing approach to exponential stability for uncertain cellular neural networks with discrete and distributed time-varying delays

This paper considers the problem of exponential stability of uncertain cellular neural networks with discrete and distribute time-varying delays. Some new delay-dependent stability condition are derived in terms of linear matrix inequality. We divide delay interval into multiple segments and employ the free-weighting matrices method to obtained some less conservative criteria. Finally, numerical examples are given to demonstrate the effectiveness and less conservativeness of the proposed methods.     

New delay-dependent stability results for discrete-time recurrent neural networks with time-varying delay

This paper studies the problem of stability analysis for discrete-time recurrent neural networks (DRNNs) with time-varying delays. By using the discrete Jensen inequality and the sector bound conditions, a new less conservative delay-dependent stability criterion is established in terms of linear matrix inequalities (LMIs) under a weak assumption on the activation functions. By using a delay decomposition method, a further improved stability criterion is also derived. It is shown that the newly obtained results are less conservative than the existing ones. Meanwhile, the computational complexity of the newly obtained stability conditions is reduced since less variables are involved. A numerical example is given to illustrate the effectiveness and the benefits of the proposed method.     

Delay-dependent stability analysis for Markovian jump systems with interval time-varying-delays

This paper proposes improved stochastic stability conditions for Markovian jump systems with interval time-varying delays. In terms of linear matrix inequalities (LMIs), less conservative delay-range-dependent stability conditions for Markovian jump systems are proposed by constructing a different Lyapunov-Krasovskii function. The resulting criteria have advantages over some previous ones in that they involve fewer matrix variables but have less conservatism. Numerical examples are provided to demonstrate the efficiency and reduced conservatism of the results in this paper.