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Convergence properties of preconditioned hermitian and skew-hermitian splitting methods for non-hermitian positive semidefinite matrices

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Mathematics of Computation 2007年第257期76卷 287-298页

作者： Bai, Zhong-Zhi Golub, Gene H. Li, Chi-Kwong Department of Mathematics Fudan University Shanghai 200433 China State Key Laboratory of Scientific Acad. of Math. and Syst. Sci. Chinese Acad. of Sci. Beijing 100080 P.O. BOX 2719 China Scientific Computing and Computational Mathematics Program Department of Computer Science Stanford University Stanford CA 94305-9025 United States Department of Mathematics College of William and Mary Williamsburg VA 23187-8795 P.O. Box 8795 United States

For the non-Hermitian and positive semidefinite systems of linear equations, we derive necessary and sufficient conditiorrs for guaranteeing the unconditional convergence of the preconditioned Hermitian and skew-Hermitian splitting iteration methods. We then apply these results to block tridiagonal linear systems in order to obtain convergence conditions for the corresponding block variants of the preconditioned Hermitian and skew-Hermitian splitting iteration methods. © 2006 American Mathematical Society.

关键词： Convergence Hermitian and skew-Hermitian splitting Non-Hermitian matrix Positive semidefinite matrix Splitting iteration method

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Uncalibrated eye-in-hand visual servoing using recursive least squares

Uncalibrated eye-in-hand visual servoing using recursive lea...

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IEEE International Conference on systems, Man and Cybernetics

作者： Miao Hao Zengqi Sun Masakazu Fujii Wei Song Candidate of State Key Laboratory of Intelligent Technology and Systems Department Computer Science & Technology Tsinghua University Beijing China Department Computer Science & Technology Tsinghua University Beijing China Corporate Research and Development Ishikawajima-Harima Heavy Industries Company Limited Yokohama Japan Software engineer of BCM Department Infosys Technologies Limited Shanghai China

In this paper, an uncalibrated dynamic visual servoing algorithm is proposed and analyzed. No calibration or robot model is needed. After a brief introduction of the development of uncalibrated visual servoing, the theoretical backgrounds and mathematical requirements of recursive least square (RLS) are stated respectively. Then the core uncalibrated visual servoing algorithm, in RLS form, or more technically, VS-RLS as well as its performance analysis, is investigated. After that, the experimental 6DOF Puma560 simulation of static and moving target tracking is demonstrated. Finally the weak and strength of the algorithm as well as the potential and promising improvements are discussed.

关键词： Visual servoing Least squares methods Resonance light scattering Heuristic algorithms Algorithm design and analysis Calibration Robots Performance analysis Target tracking Potential well

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Classification with the hybrid of manifold learning and gabor wavelet

Classification with the hybrid of manifold learning and gabo...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Zhang, Junping Shen, Chao Feng, Jufu Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China National Key Laboratory for Machine Perception School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (纸本)354034439X

While manifold learning algorithms can discover intrinsic low-dimensional manifold embedded in the high-dimensional Euclidean space, the discriminant ability of the low-dimensional subspaces obtained by the algorithms is often lower than those obtained by the conventional dimensionality reduction approaches. Furthermore, the original feature vectors may include redundancy such as high-order correlation which cannot be removed by manifold learning algorithms. To address the two problems, we first employ Gabor wavelet to remove intrinsic redundancies of images and obtain a set of over-completed feature vectors. Then a supervised manifold learning algorithm (ULLELDA) is applied to project Gabor-based data and out-of-the-samples into a common low-dimensional subspace. Experiments in two FERET face databases indicate that Gabors indeed help supervised manifold learning to remarkably improve the discriminant ability of low-dimensional subspaces. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Wavelet transforms

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An improved super-resolution with manifold learning and histogram matching

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International Conference on Biometrics, ICB 2006

作者： Chan, Tak Ming Zhang, Junping Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)3540311114

Biometric Person Authentication such as face, fingerprint, palmprint and signature depends on the quality of image processing. When it needs to be done under a low-resolution image, the accuracy will be impaired. So how to recover the lost information from down-sampled images is important for both authentication and preprocessing. Based on Super-Resolution through Neighbor Embedding algorithm and histogram matching, we propose an improved super-resolution approach to choose more reasonable training images. First, the training image are selected by histogram matching. Second, neighbor embedding algorithm is employed to recover the high-resolution image. Experiments in several images show that our improved super-resolution approach is promising for potential applications such as low-resolution mobile phone or CCTV (Closed Circuit Television) image person authentication. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Pattern matching

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Geometrical probability covering algorithm

Geometrical probability covering algorithm

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2nd International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2005

作者： Zhang, Junping Li, Stan Z. Wang, Jue Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9783540283126

In this paper, we propose a novel classification algorithm, called geometrical probability covering (GPC) algorithm, to improve classification ability. On the basis of geometrical properties of data, the proposed algorithm first forms extended prototypes through computing means of any two prototypes in the same class. Then Gaussian kernel is employed for covering the geometrical structure of data and used as a local probability measurement. By computing the sum of the probabilities that a new sample to be classified to the set of prototypes and extended prototypes, the classified criterion based on the global probability measurement is achieved. The proposed GPC algorithm is simple but powerful, especially, when training samples are sparse and small size. Experiments on several databases show that the proposed algorithm is promising. Also, we explore other potential applications such as outlier removal with the proposed GPC algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Algorithms

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Single camera 3D lane detection and tracking based on EKF for urban intelligent vehicle

Single camera 3D lane detection and tracking based on EKF fo...

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IEEE International Conference on Vehicular Electronics and Safety, ICVES 2006

作者： Min, Tian Fuqiang, Liu Zhencheng, Hu IEEE Key Laboratory of Embedded System and Service Computing Ministry of Education China Electronic and Information Engineering Department Tongji University Shanghai 201804 China Department of Computer Science Kumamoto University Kumamoto 860-8555 Japan

ISBN: (纸本)1424407591

Road boundary detection and tracking is an important and integral function in advanced driver-assistance system. This paper proposes an algorithm, which can follow multi-kinds of lane, straight and curved, quickly and robustly. The algorithm uses several masks to extract blobs of road markings, combining with KNN function to remove the disturbance. Further more, road is modeled as a 3D surface, and some important parameters of current lane are provided on real-time by tracking based on Extended Kalman Filter (EKF). The results of experiments, which have been done in urban road, show that the algorithm is adapted to many road conditions. Even in a complex driving environment, it also has a good performance. © 2006 IEEE.

关键词： Extended Kalman filters

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Performance evaluation of allgather algorithms on terascale Linux cluster with Fast Ethernet

Performance evaluation of allgather algorithms on terascale ...

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8th International Conference on High-Performance computing in Asia-Pacific Region

作者： Chen, Jing Zhang, Linbo Zhang, Yunquan Yuan, Wei Department of Computer Science University of Science and Technology of China China Lab. of Parallel Computing Institute of Software CAS China State Key Laboratory of Computer Science China Academy of Mathematics and Systems Sciences CAS China

ISBN: (纸本)0769524869

We report our work on evaluating performance of several MPI Allgather algorithms on Fast Ethernet. These algorithms are ring, recursive doubling, Bruck, and neighbor exchange. The first three algorithms are widely used today. The neighbor exchange algorithm which was recently proposed by the authors incorporates pair-wise exchange, and is expected to perform better with certain configurations, mainly when using TCP/IP over Ethernet. We tested the four algorithms on terascale Linux clusters DeepComp 6800 and DAWNING 4000A using TCP/IP over Fast Ethernet. Results show that our neighbor exchange algorithm performs the best for long messages, the ring algorithm performs the best for medium-size messages and the recursive doubling algorithm performs the best for short messages.

关键词： computer networks

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Investigating manifold learning algorithms based on magnification factors and principal spread directions

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Jisuanji Xuebao/Chinese Journal of computers 2005年第12期28卷 2000-2009页

作者： He, Li Zhang, Jun-Ping Zhou, Zhi-Hua Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences Shanghai 200433 China Department of Computer Science and Engineering School of Mathematical Sciences Fudan University Shanghai 200433 China National Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China

As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMAP) and Locally Linear Embedding (LLE). The approaches can be used for discovering the intrinsic dimensions of nonlinear high-dimensional data effectively and aim researchers to analyze the data better. How to quantitatively analyze the relationship between the intrinsic dimensions and the observation space, however, has fewer reports. And thus further works in manifold learning may have suffered some difficulties. The paper focuses on two kinds of manifold learning algorithms (ISOMAP, LLE), and discusses magnification factors and principal spread directions from the observation space to the intrinsic low-dimensional space. Also the corresponding algorithm is proposed. Experiments show the effectiveness and advantages of the research.

关键词： Learning algorithms

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Adaptive nonlinear auto-associative modeling through manifold learning

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9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005

作者： Zhang, Junping Li, Stan Z. Intelligent Information Processing Laboratory Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences China National Laboratory of Pattern Recognition Center for Biometrics and Security Research Institute of Automation Beijing 100080 China

ISBN: (纸本)3540260765

We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separately and recognition thereby. Unlike traditional supervised manifold learning algorithm, the proposed ANAM algorithm has several advantages: 1) it implicitly embodies discriminant information because the suboptimal parameters of ANAM are determined based on error rate of the validation set. 2) it avoids the curse of dimensionality without loss accuracy because recognition is completed in the original space. Experiments on character and digit databases show that the advantages of the proposed ANAM algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Learning systems

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The Reasoning Mechanism of Fuzzy Cognitive Maps

The Reasoning Mechanism of Fuzzy Cognitive Maps

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Xiang-Feng Luo Er-Lin Yao The Key Laboratory of Grid Research Department of Computer Engineering and Science Shanghai University Shanghai China China Knowledge Grid Research Group Institute of Computing Technology Chinese Academy and Sciences Beijing China

Fuzzy cognitive maps (FCMs) can represent and reason causal knowledge with stronger semantics. And the causal knowledge widely exists in knowledge grid. To provide information services with stronger semantics in Knowledge Grid, we need to know the reasoning mechanism and the characteristics of FCMs. In this paper, we have proved that the reasoning process of FCMs is a discrete topological semi- dynamic system. This theory can help us analyze the reasoning process and find the new characteristics of FCMs, which can guide us using FCMs to provide intelligent information services flexibly in knowledge Grid.

关键词： Fuzzy cognitive maps Grid computing Knowledge engineering computers Knowledge management Electrical equipment industry Electronics industry Industrial control Industrial economics Control systems

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