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International Conference on Image and Graphics (ICIG)

作者： Hong Cheng Hong Liu Quanbing Zhang Sui Wei Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China College of Electronic Science and Technology Anhui University Hefei China

ISBN: (纸本)9781424452378

The transport-of-intensity equation describes the internal relationship between the intensity and phase distribution while wave is propagating in the mobile space. So the phase distribution can be solved by the use of the equation. It is an important measurement of non-interferometry. A new phase retrieval based on transport-of-intensity equation is presented. This method has the advantage of measuring only the close-up space on the plane of the intensity of light to the reconstruction of phase space. The problem of phase retrieval is translated into minimum of energy functional with linear convolution and total variation regularization. The one and two dimension experiment results show the correctness and validity of the algorithm.

关键词： Equations Phase measurement Space technology Holography Optical interferometry Extraterrestrial measurements Holographic optical components Image reconstruction signal processing algorithms Diffraction

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A Threshold RSA Signature Scheme with Traceable Signers

A Threshold RSA Signature Scheme with Traceable Signers

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International Conference on E-Business and Information System Security, EBISS

作者： Runhua Shi Hong Zhong Key Laboratory of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei China School of Computer Science and Technology Anhui University Hefei China

This paper proposed a threshold RSA signature with traceable signers. In such scheme, there is a trusted center (TC), which generates all system parameters, the secret keys and the corresponding public keys of the group and all members, and exists a designated clerk, which creates a warrant recording the identities of the signers and other import information. Any t members can collaboratively generate the group signature with the help of the clerk, who verifies the validity of the partial signatures and combines them to the group signature. Any one can verify the correctness of the group signature by the public information and trace out to find the identities of the signers by the warrant.

关键词： Public key Forgery Digital signatures Laboratories signal processing Collaboration Cryptography Computer science Computer security Information security

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A point pattern matching algorithm based on minimize spanning tree and Fiedler vector

A point pattern matching algorithm based on minimize spannin...

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1st International Conference on Information Science and Engineering, ICISE2009

作者： Xuan, Shan-Li Liang, Dong Zhu, Ming Fan, Yi Zheng Wang, Nian Key Lab. Intelligent Computing and Signal Ministry of Education Anhui University Hefei 230039 China School of Mathematical Sciences Anhui University Hefei 230039 China School of Computer and Information HeFei University of Technology Hefei 230009 China

ISBN: (纸本)9780769538877

Based on the minimize spanning tree and Fiedler vector, a new feature matching algorithm is proposed in this paper. Firstly, a weighted complete graph is constructed with the feature points of each image respectively, then search the minimal spanning tree in each complete graph. Secondly, perform spectral decomposition on the Gaussian-weighted Laplace matrix of the minimize spanning tree respectively, and divide the feature points into several different sets based on the vector(Fiedler vector) corresponding to the second smallest eigenvalue of Laplace matrix , then the corresponding relation between sets is obtained. And construct Gaussian-weighted Laplace matrices between the corresponding sets, then submit the matrices to spectral decomposition. Finally, complete the feature matching by constructing matching matrix with eigenvalues and eigenvectors. Experiment results indicate that the algorithm has a high accuracy. ©2009 IEEE.

关键词： Vectors

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The Implementation of the Web Mining Based on XML Technology

The Implementation of the Web Mining Based on XML Technology

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International Conference on Computational Intelligence and Security

作者： Cheng Zheng Yong Fang Yaping Shen Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

ISBN: (纸本)9781424454112

The rapid development of the Web technology makes the Web mining become the focus of the current data mining, and the XML technology also becomes the standard of the data exchange on the Web. The paper introduces the Web mining technology, implements a frame of the Web mining based on the XML technology according to the advantage of XML in the data description, describes the implementation process of specific Web mining, and puts forward a promoting scheme on solving XML documents with VTD which solves the difficult mining problem on the Web caused by the most of the non-structure information.

关键词： Web mining XML HTML Data mining Web pages educational technology Data acquisition Databases Computational intelligence Paper technology

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Method with the center of graph for point pattern matching

Method with the center of graph for point pattern matching

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9th International Conference on Electronic Measurement and Instruments, ICEMI 2009

作者： Xuan, Shanli Liang, Dong Zhu, Ming Fan, Yizheng Wang, Nian Key Lab. Intelligent Computing and Signal Ministry of Education Anhui University Hefei 230039 China School of Computer and Information HeFei University of Technology Hefei 230009 China School of Mathematical Sciences Anhui University Hefei 230039 China

ISBN: (纸本)9781424438624

Based on the center of graph, a point pattern feature matching method is proposed here. Firstly, a weighted complete graph is constructed with the feature points of each image, and then the center of each graph is found respectively. With the vertex sets of the centers, the feature points are divided into several layers according to the distance from the center, and then the corresponding relation between layers is obtained. Secondly, the Gaussian-weighted Laplace matrices are constructed between the corresponding layers. And then the matrices are submitted to singular-value decomposition(SVD). Finally, represent the feature points with eigenvectors obtained from SVD, and then construct matching matrix to obtain the final matching results. Synthetic data and real world data both indicate that our method has a higher accuracy than theirs, and it can deal with the matching problem with more feature points effectively. ©2009 IEEE.

关键词： Singular value decomposition

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Method with the Center of Graph for Point Pattern Matching

Method with the Center of Graph for Point Pattern Matching

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2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI'2009)

作者： Shanli Xuan Dong Liang Nian Wang Ming Zhu Yizheng Fan School of Computer & Information HeFei University of TechnologyHefei230009China Key Lab Intelligent Computing & Signal Ministry of Education Anhui UniversityHefei230039China Key Lab Intelligent Computing & Signal Ministry of Education Anhui UniversityHefei230039China Sch

Based on the center of graph,a point pattern feature matching method is proposed ***,a weighted complete graph is constructed with the feature points of each image,and then the center of each graph is found *** the vertex sets of the centers,the feature points are divided into several layers according to the distance from the center,and then the corresponding relation between layers is ***,the Gaussian-weighted Laplace matrices are constructed between the corresponding layers. And then the matrices are submitted to singular-value decompositionfSVD).Finally,represent the feature points with eigenvectors obtained from sVD,and then construct matching matrix to obtain the final matching *** data and real world data both indicate that our method has a higher accuracy than theirs,and it can deal with the matching problem with more feature points effectively.

关键词： feature point center of graph Laplace matriz matching.

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3D imaging algorithm and implement for through-wall synthetic aperture radar

3D imaging algorithm and implement for through-wall syntheti...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Jiabing Zhu Yi Hong Liang Tao East China Research Institute of Electronic East China Research Institute of Electronic Engineering Hefei China Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (纸本)9781424444793;9781424444809

Typical synthetic aperture radar (SAR) images are two-dimensional, providing range and azimuth information, but furnish few details with respect to elevation. First of all, one approach to extend SAR to three-dimensional imaging is considered. The simplest implementation of this would replace the single antenna element by a linear array oriented vertically. Secondly, the outlining data and image processing for a three-dimensional application is introduced in detail in the paper. Finally, simulation results show that the proposed algorithm is effective, while maintaining good image quality in terms of the reconstructed target response.

关键词： Azimuth Linear antenna arrays signal processing algorithms Synthetic aperture radar Spaceborne radar Image reconstruction Radar imaging Radar signal processing Pulse compression methods Image processing

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Maximizing Spectral Radius of Trees with Given Maximal Degree

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Journal of Mathematical Research and Exposition 2009年第5期29卷 806-812页

作者： FAN Yi Zheng ZHU Min Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education of the People's Republic of China Anhui University Anhui 230039 China School of Mathematical Sciences Anhui University Anhui 230039 China

In this paper, we characterize the trees with the largest Laplacian and adjacency spectral radii among all trees with fixed number of vertices and fixed maximal degree, respectively.

关键词： trees maximal degree Laplacian eigenvalue adjacency eigenvalue spectral radius.

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A Framework for Error-Tolerant Scheme in Pervasive computing

A Framework for Error-Tolerant Scheme in Pervasive Computing

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International Conference on education Technology and Computer, ICETC

作者： Jian-quan Ouyang Dian-xi Shi Bo Ding Xiao Li Huai-min Wang Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan University China School of Computer National University of Defense Technology Changsha China

Open and dynamic pervasive computing environments make fault detection and error recovery challenging. In this paper, we present a policy based framework for error-tolerant scheme in pervasive computing. As policy-based scheme can separate the business logic (rules) from the controls (programming code) of the implementations, it is typically more flexible and adaptable than non-policy-based approach. Moreover, the policy mechanism is based on not only event-condition-action rules, but also the-Separation-of-Concerns-principle for easily extensible to support the error recovery scheme.

关键词： Pervasive computing Computer architecture Logic programming Computer science education educational technology Computer errors Fault detection Prototypes Fault tolerant systems Application software

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A Point Pattern Matching Algorithm Based on Minimize Spanning Tree and Fiedler Vector

A Point Pattern Matching Algorithm Based on Minimize Spannin...

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International Conference on Information Science and Engineering (ICISE)

作者： Shan-li Xuan Dong Liang Ming Zhu Yi zheng Fan Nian Wang School of Computer & Information HeFei University of Technology Hefei China Key Laboratory Intelligent Computing & Signal Ministry of Education Anhui University Hefei China School of Mathematical Sciences Anhui University Hefei China

ISBN: (纸本)9781424449095

Based on the minimize spanning tree and Fiedler vector, a new feature matching algorithm is proposed in this paper. Firstly, a weighted complete graph is constructed with the feature points of each image respectively, then search the minimal spanning tree in each complete graph. Secondly, perform spectral decomposition on the Gaussian-weighted Laplace matrix of the minimize spanning tree respectively, and divide the feature points into several different sets based on the vector (Fiedler vector) corresponding to the second smallest eigenvalue of Laplace matrix, then the corresponding relation between sets is obtained. And construct Gaussian-weighted Laplace matrices between the corresponding sets, then submit the matrices to spectral decomposition. Finally, complete the feature matching by constructing matching matrix with eigenvalues and eigenvectors. Experiment results indicate that the algorithm has a high accuracy.

关键词： Pattern matching Matrix decomposition Tree graphs Eigenvalues and eigenfunctions Gaussian processes Laplace equations Information science Computer science education educational technology Computer vision

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