基于FPGA的运动目标远程监视系统设计

运动目标检测是智能安防系统的重要组成部分,为了满足安防系统远距离监视目标以及视频传输实时性等需求,设计了一种基于FPGA平台的运动目标远程监视系统;该系统以Xilinx公司的Artix7系列FPGA芯片为核心,通过OV5640摄像头实现视频图像的采集,将采集到的图像进行灰度化处理,并通过DDR3存储器缓存处理后的图像,采用帧间差分法运动目标检测技术实现对多个运动物体的检测与标记,将检测结果通过以太网的UDP协议传输到上位机实时显示;实验结果表明,在图像分辨率为640*480时,以太网UDP传输速度为133Mbit/s,视频图像帧率为26fps,大于人眼的可视帧率24fps,满足视频传输实时性的要求,同时该系统能够远距离、高效地检测与跟踪多个运动目标,相比于其他系统具有可远程实时检测、小型化、低功耗的特点,可进一步应用到智能安防系统中。     

基于GaBP算法的快速潮流计算方法

研究在潮流迭代求解过程中雅可比矩阵方程组的迭代求解方法及其收敛性。首先利用PQ分解法进行潮流迭代求解,并针对求解过程中雅可比矩阵对称且对角占优的特性,对雅可比矩阵方程组采用高斯置信传播算法(GaBP)进行求解,再结合Steffensen加速迭代法以提高GaBP算法的收敛性。对IEEE118、IEEE300节点标准系统和两个波兰互联大规模电力系统进行仿真计算后结果表明：随着系统规模的增长,使用Steffensen加速迭代法进行加速的GaBP算法相对于基于不完全LU的预处理广义极小残余方法(GMRES)具有更好的收敛性,为大规模电力系统潮流计算的快速求解提供了一种新思路。     

移动机器人避障行为酶数值膜控制器

为了兼顾膜控制器控制下的移动机器人行走速度和避障效果,提出了一种基于酶数值膜系统的自适应巡航速度避障控制方法.该方法采用酶数值膜系统结构,利用膜之间的信息交流,实现多个膜融合多个传感器的距离信息,根据融合距离信息自适应调节巡航速度,使移动机器人能够有效的避开障碍物,同时兼顾无障碍物时移动机器人行走速度.基于移动机器人Pioneer3-DX的仿真和实物实验表明：该方法设计的酶数值膜控制器可行且避障控制效果更优.     

Solving separable elliptic equations by the block stride reduction algorithm

A comparison of the Buneman version of the block cyclic reduction (BCR) algorithm and Stride Reduction (BSR) based on polynomial factorization for separable elliptic equations with Dirichlet boundary conditions is presented. This study was initiated by an interest in the parallel computing techniques that can be used to increase the computational efficiency of these model problems     

Motion planning of multiple mobile robots by a combination of learned visibility graphs and virtual impedance

A motion planning algorithm for multiple mobile robots is proposed in this paper. A hierarchical architecture with two layers 'learned visibility graph layer (upper layer)' and 'virtual impedance layer (lower layer)' (one of the potential field planning method) is presented. This system has the following characteristics: (1) is applicable to unknown dynamic environments, (2) is applicable to distributed multiple robot systems and (3) is capable of adequate path generation and motion. At the upper layer, efficient exploration of environments makes it possible to generate sub-shortest paths that avoid static obstacles. At the lower layer, on-line avoidance can be made with virtual impedance against moving obstacles such as other robots. Simulation results show the validity of the proposed method.     

Stabilizability for nonlinear systems of difference equations

The stabilization problem for a class of infinite‐dimensional discrete‐time nonlinear systems is discussed. Under an appropiate growth condition on the nonlinear perturbation combined with the ‘freezing’ method to discrete‐time systems on Banach spaces, we establish explicit conditions for global feedback exponential stabilizability, and these conditions are easy to construct and to verify. This approach will allow us to avoid the construction of Lyapunov's functions in some situations. Copyright © 2009 John Wiley & Sons, Ltd.     

About the convergence of the method of the ‘reactive energy minimization principle’†

In a previous work, we have proposed a way, founded on the ‘reactive energy minimization principle’, for improving the accuracy of Kochenburger's method in the study of non-linear systems. We prove, here, the convergence of this algorithm. In order to do so, we prove firstly, with the help of Tsypkin's theory that the algorithm is exact for on-off closed-loop systems. From this result and by using some theorems on functional continuity which have been established elsewhere, we prove that the proposition is still true, for a greater set of systems.

Dans un précédent travail, nous avons proposé une méthode basée sur le principe de minimisation de l'énergio réactive, pour améliorer la précision du premier harmonique dans l'tude des systémes non linéaires. On démontre ici la convergence de cet algorithme. Pour cela, on démontre d'abord, à l'aide de la théorie de Tsypkin, que 1'algonthme est exact pour les systémes asservis par plus ou moins. A partir de ce résultat, utilisant divers théorèmes de continuité fonctionnelle établis par ailleurs, on montre qu'il est encore exact pour une plus grande classe do syst`mes.     

利用提升-预估法设计离散时间时滞线性系统的预见控制器

研究一类既有状态时滞又有输入时滞的离散时间线性系统的预见控制问题.分别使用离散提升技术和变量替换法将系统中的状态时滞和输入时滞消掉,得到一个无时滞的系统.在此基础上,使用预见控制理论和状态预估法得到一个带有状态时滞补偿、输入时滞补偿和参考信号预见补偿的控制器.针对不同的时滞使用不同的方法进行消除,有效地降低了增广系统的维数.最后,通过一个数值算例验证了所提出设计方法的有效性.     

On the implementation of bytecode compression for interpreted languages

This paper describes a new method for code space optimization for interpreted languages called LZW‐CC . The method is based on a well‐known and widely used compression algorithm, LZW , which has been adapted to compress executable program code represented as bytecode. Frequently occurring sequences of bytecode instructions are replaced by shorter encodings for newly generated bytecode instructions. The interpreter for the compressed code is modified to recognize and execute those new instructions. When applied to systems where a copy of the interpreter is supplied with each user program, space is saved not only by compressing the program code but also by automatically removing the unused implementation code from the interpreter. The method's implementation within two compiler systems for the programming languages Haskell and Java is described and implementation issues of interest are presented, notably the recalculations of target jumps and the automated tailoring of the interpreter to program code. Applying LZW‐CC to nhc98 Haskell results in bytecode size reduction by up to 15.23% and executable size reduction by up to 11.9%. Java bytecode is reduced by up to 52%. The impact of compression on execution speed is also discussed; the typical speed penalty for Java programs is between 1.8 and 6.6%, while most compressed Haskell executables run faster than the original. Copyright © 2008 John Wiley & Sons, Ltd.     

反映人的认知习惯的商品检索方法

目的 便捷的商品检索是用户网络购物体验良好的关键环节。由于电商对商品描述方式的规范性要求以及用户对商品属性理解差异等问题，基于关键词的检索方法在商品检索的应用并不理想。近年来，以图搜图的检索方式在各大电商平台上得到越来越多的应用，但检索结果往往不尽如人意。为此，提出了一种新的检索思路，从商品外观设计特征出发，将人们对商品的认知模式引入到商品图片的检索过程，从而获得更符合人们预期的检索结果。方法 以时尚女包商品为例，在分析设计师的设计规范的基础上，将外观设计特征分解为形状特征、颜色特征和设计元素特征。利用深度卷积神经网络建模、提取特征，并使用哈希方法和Top3类内检索算法加快检索速度。结果 利用建立的商品数据集构建3个对应的特征模型，并进行分类识别和图像检索实验。结果表明，各个模型Top1的识别准确率均小于95%，而Top3的识别准确率均在98.5%以上；商品检索速度加快了将近3.5倍。实验及用户调查结果表明，本文提出的检索方法与淘宝、百度图片等基于图像的检索工具相比，检索结果更为多样，与原图像相似度更高。结论 本文提出的从商品外观设计规范出发、与人的认知模式相结合的商品检索方法，更能满足用户的检索意图，可用于时尚女包商品检索，对基于图像的其他商品的检索方法的研究具有借鉴意义。     

Editorial of the Special Issue on Manifold Learning

In many information analysis tasks, one is often confronted with thousands to millions dimensional data, such as images, documents, videos, web data, bioinformatics data, etc. Conventional statistical and computational tools are severely inadequate for processing and analysing high-dimensional data due to the curse of dimensionality, where we often need to conduct inference with a limited number of samples. On the other hand, naturally occurring data may be generated by structured systems with possibly much fewer degrees of freedom than the ambient dimension would suggest. Recently, various works have considered the case when the data is sampled from a submanifold embedded in the much higher dimensional Euclidean space. Learning with full consideration of the low dimensional manifold structure, or specifically the intrinsic topological and geometrical properties of the data manifold is referred to as manifold learning, which has been receiving growing attention in our community in recent years. This special issue is to attract articles that (a) address the frontier problems in the scientific principles of manifold learning, and (b) report empirical studies and applications of manifold learning algorithms, including but not limited to pattern recognition, computer vision, web mining, image processing and so on. A total of 13 submissions were received. The papers included in this special issue are selected based on the reviews by experts in the subject area according to the journal''s procedure and quality standard. Each paper is reviewed by at least two reviewers and some of the papers were revised for two rounds according to the reviewers'' comments. The special issue includes 6 papers in total: 3 papers on the foundational theories of manifold learning, 2 papers on graph-based methods, and 1 paper on the application of manifold learning to video compression. The papers on the foundational theories of manifold learning cover the topics about the generalization ability of manifold learning, manifold ranking, and multi-manifold factorization. In the paper entitled ``Manifold Learning: Generalizing Ability and Tangential Proximity'', Bernstein and Kuleshov propose a tangential proximity based technique to address the generalized manifold learning problem. The proposed method ensures not only proximity between the points and their reconstructed values but also proximity between the corresponding tangent spaces. The traditional manifold ranking methods are based on the Laplacian regularization, which suffers from the issue that the solution is biased towards constant functions. To overcome this issue, in the paper entitled ``Manifold Ranking using Hessian Energy'', Guan et al. propose to use the second-order Hessian energy as regularization for manifold ranking. In the paper entitled ``Multi-Manifold Concept Factorization for Data Clustering'', Li et al. incorporate the multi-manifold ensemble learning into concept factorization to better preserve the local structure of the data, thus yielding more satisfactory clustering results. The papers on graph-based methods cover the topics about label propagation and graph-based dimensionality reduction. In the paper entitled ``Bidirectional Label Propagation over Graphs'', Liu et al. propose a novel label propagation algorithm to propagate labels along positive and negative edges in the graph. The construction of the graph is novel against the conventional approach by incorporating the dissimilarity among data points into the affinity matrix. In the paper entitled ``Locally Regressive Projections'', Lijun Zhang proposes a novel graph-based dimensionality reduction method that captures the local discriminative structure of the data space. The key idea is to fit a linear model locally around each data point, and then use the fitting error to measure the performance of dimensionality reduction. In the last paper entitled ``Combining Active and Semi-Supervised Learning for Video Compression'', motivated from manifold regularization, Zhang and Ji propose a machine learning approach for video compression. Active learning is used to select the most representative pixels in the encoding process, and semi-supervised learning is used to recover the color video in the decoding process. One remarking property of this approach is that the active learning algorithm shares the same loss function as the semi-supervised learning algorithm, providing a unified framework for video compression. Many people have been involved in making this special issue possible. The guest editor would like to express his gratitude to all the contributing authors for their insightful work on manifold learning. The guest editor would like to thank the reviewers for their comments and useful suggestions in order to improve the quality of the papers. The guest editor would also like to thank Prof. Ruqian Lu, the editor-in-chief of the International Journal of Software and Informatics, for providing the precious opportunity to publish this special issue. Finally, we hope the reader will enjoy this special issue and find it useful.     

A novel architecture of dynamically reconfigurable fused multiply–adder for digital signal processing

Introduction

Multiply-accumulate operation is the most fundamental operation in digital signal processing for image processing, robotics and automatic control. In this paper, a novel architecture of dynamically reconfigurable fused multiply-adder (FMA) is proposed.

Methods

Dynamic reconfiguration is a method that can change the circuit configuration without stop of operation. The proposed circuit provides the following four calculation modes by dynamic reconfiguration: (1) complex number FMA mode, (2) real number FMA mode, (3) complex number parallel calculation mode, and (4) real number parallel calculation mode.  The data format is single precision floating point format based on IEEE754. The proposed circuit was designed using Verilog-HDL. It was simulated by logic circuit simulator, and implemented on FPGA.

Result

As a result of circuit synthesis, we confirmed the reduction of resource in the proposed circuit. Furthermore, we confirmed proper result for each calculation mode by logic simulation and experiment on FPGA.

Conclusion

The proposed circuit provides the four calculation modes by dynamic reconfiguration. We confirmed the reduction of resource and proper result for each calculation mode.     

加权KNN的图文数据融合分类

目的 图文数据在不同应用场景下的最佳分类方法各不相同,而现有语义级融合算法大多适用于图文数据分类方法相同的情况,若将其应用于不同分类方法时由于分类决策基准不统一导致分类结果不理想,大幅降低了融合分类性能。针对这一问题,提出基于加权KNN的融合分类方法。方法 首先,分别利用softmax多分类器和多分类支持向量机(SVM)实现图像和文本分类,同时利用训练数据集各类别分类精确度加权后的图像和文本正确判别实例的分类决策值分别构建图像和文本KNN模型;再分别利用其对测试实例的图像和文本分类决策值进行预测,通过最邻近k个实例属于各类别的数目确定测试实例的分类概率,统一图像和文本的分类决策基准;最后利用训练数据集中图像和文本分类正确的数目确定测试实例中图像和文本分类概率的融合系数,实现统一分类决策基准下的图文数据融合。结果 在Attribute Discovery数据集的图像文本对上进行实验,并与基准方法进行比较,实验结果表明,本文融合算法的分类精确度高于图像和文本各自的分类精确度,且平均分类精确度相比基准方法提高了4.45%;此外,本文算法对图文信息的平均整合能力相比基准方法提高了4.19%。结论 本文算法将图像和文本不同分类方法的分类决策基准统一化,实现了图文数据的有效融合,具有较强的信息整合能力和较好的融合分类性能。     

An investigation of Newton-Sketch and subsampled Newton methods

ABSTRACT

Sketching, a dimensionality reduction technique, has received much attention in the statistics community. In this paper, we study sketching in the context of Newton's method for solving finite-sum optimization problems in which the number of variables and data points are both large. We study two forms of sketching that perform dimensionality reduction in data space: Hessian subsampling and randomized Hadamard transformations. Each has its own advantages, and their relative tradeoffs have not been investigated in the optimization literature. Our study focuses on practical versions of the two methods in which the resulting linear systems of equations are solved approximately, at every iteration, using an iterative solver. The advantages of using the conjugate gradient method vs. a stochastic gradient iteration are revealed through a set of numerical experiments, and a complexity analysis of the Hessian subsampling method is presented.     

基于系数图法的多输入多输出系统控制器设计方法

多输入多输出系统的交互作用会限制适用于单输入单输出系统的多种先进设计方法的使用,且多数关于多输入多输出系统控制研究只重视消除交互作用的影响,忽略系统控制问题,这样不但弱化系统的鲁棒性,且设计过程复杂,解耦后系统阶次也较高.鉴于此,提出一种基于系数图法的多入多出系统的控制器设计方法,将多输入多输出系统解耦问题转化为参数优化问题.首先,给出目标函数和两个线性约束条件,通过在频域基于粒子群算法优化目标函数,从而设计补偿器实现解耦;其次,基于系数图法确定控制器结构及参数整定,兼顾系统的稳定性和鲁棒性;最后,通过仿真实验验证所提出方法的有效性.     

A 3‐D unconditionally stable precise integration time domain method for the numerical solutions of Maxwell's equations in circular cylindrical coordinates

An unconditionally stable precise integration time‐domain method is extended to 3‐D circular cylindrical coordinates to solve Maxwell's equations. In contrast with the cylindrical finite‐difference time‐domain method, not only can it remove the stability condition restraint, but also make the numerical dispersion independent of the time‐step size. Numerical results are presented to demonstrate the effectiveness of this method. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

碳限额与交易机制和消费者低碳偏好下的供应链减排及融资策略

在碳限额与交易机制和消费者对低碳产品存在偏好的背景下,考虑由一个资金约束的制造商与一个资金充裕的零售商构成的供应链,针对银行贷款(BF)、提前支付折扣(APD)和提前支付回购(APB)3种融资方式,构建制造商主导的以企业利润最大化为目标的博弈模型,研究不同融资方式下低碳供应链的减排与定价决策,以及制造商的融资方式选择问题.研究表明:1)在3种融资方式下,减排投资成本系数的增加会降低制造商的最优单位产品碳减排量.2)提前支付下制造商的最优单位产品碳减排量始终高于BF方式.当碳交易价格较高或减排投资成本系数较高时,APB方式下制造商的碳减排量最高;否则,APD方式下制造商的碳减排量最高.3)与BF方式相比,提前支付更能提升制造商的利润,且制造商在APB方式下获利最多.     

Metameric failure assessment and reduction between RGB and laser phosphor projectors

Metameric failure is commonly observed when different types of displays reproduce the same color, as it is defined by a colorimetry system, but the outputs do not match visually. Metameric failure is impacted by the used colorimetry system and the relation between the involved displays' spectral power distributions (SPDs). In this work, we assess the metameric failure between the upcoming types of theatrical projectors, RGB laser, and laser phosphor (LaPH) and propose a method to reduce it. Our analysis starts by evaluating the performance of existing colorimetry systems in terms of metameric failure reduction. Among the colorimetry systems tested, the CIE 2006 2° (CIE06 2°) system resulted in the least observed metameric failure for a large portion of the participants but not their absolute majority (>50%). The limited performance of existing colorimetry systems led us to questioning the feasibility of successful perceptual color matching between the two projectors. To explore and potentially rule-out this scenario, we performed a subjective color matching experiment. The analysis of the results revealed the key role that the projectors' SPD differences play on color matching. Based on the observations of the first two studies, we propose a novel colorimetry system that reduces further than existing colorimetry the systems the metameric failure between RGB and LaPH projectors. Our proposed system is a modified version of CIE06–2° that accounts for the spectral differences of the two light sources. Evaluation showed that our solution outperforms existing colorimetry systems.     

Parallel solution of dense linear systems using diagonalization methods

We study the parallel implementation of two diagonalization methods for solving dense linear systems: the well known Gauss-Jordan method and a new one introduced by Huard. The number of arithmetic operations performed by the Huard method is the same as for Gaussian elimination, namely 2n ³/3, less than for the Jordan method, namely n ³. We introduce parallel versions of these methods, compare their performances and study their complexity. We assume a shared memory computer with a number of processors p of the order of n, the size of the problem to be solved, We show that the best parallel version for Jordan's method is by rows whereas the best one for Huard's method is by columns. Our main result states that for a small number of processors the parallel Huard method is faster than the parallel Jordan method and slower otherwise. The separation is obtained for p = 0.44n.     

Reducibility: A ubiquitous method in lambda calculus with intersection types

A general reducibility method is developed for proving reduction properties of lambda terms typeable in intersection type systems with and without the universal type Ω. Sufficient conditions for its application are derived. This method leads to uniform proofs of confluence, standardization, and weak head normalization of terms typeable in the system with the type Ω. The method extends Tait's reducibility method for the proof of strong normalization of the simply typed lambda calculus, Krivine's extension of the same method for the strong normalization of intersection type system without Ω, and Statman-Mitchell's logical relation method for the proof of confluence of βη-reduction on the simply typed lambda terms. As a consequence, the confluence and the standardization of all (untyped) lambda terms is obtained.