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Application of AWE to scattering analysis of the double-negative medium

Application of AWE to scattering analysis of the double-nega...

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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

作者： Sun, Yu-Xin Chen, Ming-Sheng Wu, Xian-Liang Yang, Mei Wang, Hui Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China School of Information Science and Technology University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781424469062

The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band. ©2010 IEEE.

关键词： Method of moments

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Compressive sensing for wide-angle analysis

Compressive sensing for wide-angle analysis

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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

作者： Du, Hong-Mei Chen, Ming-Sheng Wu, Xian-Liang Lu, Si-Long Mei, Yi-Cai Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei 230029 China Department of Physics and Electronic Engineering Hefei Normal University Hefei 230601 China School of Information Science and Technology University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781424469062

A new incident source with different angles was constructed for dealing with wide-angle scattering problems. Considering the impendence matrix in method of moments (MOM) is independent from incident angles, the equivalent relationship between induced current and the measured CS-current was build, while the CS-current can be computed directly under the new incident source. Finally, we can reconstruct the induce current by utilizing the theory of compressive sensing (CS). Compared with traditional MOM, the computational complexity can be greatly reduced. ©2010 IEEE.

关键词： Method of moments

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An Efficient Technique for Extracting Singularity Arising in RCS Computation of Cylindrical Antenna

An Efficient Technique for Extracting Singularity Arising in...

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2010 International Conference on Microwave and Millimeter Wave Technology(2010国际微波与毫米波技术会议 ICMMT2010)

作者： Jing Li Yufa Sun Key Lab. of Intelligent Computing & Signal Processing Ministry Education Anhui University Hefei P.R.China 230039

Ana\ysis of electromagnetic scattering characteristics from wire antennas using method of moments has been performed over the past decades. In this paper, an efficient technique is adopted to evaluate the potential and reaction integrals arising in radar cross section (RCS) computation of cylindrical antenna by method of moments. The singularity of potential and reaction integrals is extracted through the semi-analytical method. The induced current on the surface and RCS of cylindrical antenna are calculated. Numerical examples are presented to illustrate the computational accuracy and efficiency of the proposed technique.

关键词： cylindrical antenna singularity radar cross section

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Inferring Protein Annotation from Topological Structural Analysis on Protein Interaction Network

Inferring Protein Annotation from Topological Structural Ana...

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Dengdi Sun Jin Fan Haifeng Zhao Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 P.R.China

As more and more high-throughput protein-protein interactions data are collected, a large fraction of newly discovered proteins have an unknown functional role. A challenge to the scientific community is to assign these newly proteins with a biological function that can be verified by experiment. On the basis of thorough analysis of existing protein function prediction, we take double direction enumeration method combined with the distance constrains to find protein pathway, and propose a new predicting model based on topological structural of protein-protein interaction (PPI) network and protein pathway, which greatly increases the speed of the algorithm. To validate the method, the Yeast Saccharomyces cerevisiae protein-protein interaction network and corresponding protein pathways are analyzed. Comparing with other methods, our results can substantially improve the accuracy and robustness of functional annotation.

关键词： Proteins Fungi Databases Computer networks Biological system modeling Predictive models Organisms signal analysis Sun intelligent networks

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A Network-based Approach for Protein Functions Prediction Using Locally Linear Embedding

A Network-based Approach for Protein Functions Prediction Us...

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Haifeng Zhao Dengdi Sun Rifeng Wang Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 P.R.China

Inferring protein functions from different data sources is a challenging task in the post-genomic era, as a large number of crude protein structures from structural genomics project are now solved without their biochemical functions characterized. Recently, many different methods have been used to predict protein functions including those based on Protein-Protein Interaction (PPI), structure, sequence relationship, gene expression data, etc. Among these approaches, methods based on protein interaction data are very promising. In this paper, we studied a network-based method using locally linear embedding (LLE). LLE is a robust learning algorithm that manipulates dimensionality reduction, neighborhood-preserving embedding for high-dimensional data. We first embed both annotated and unannotated proteins in a low dimensional Euclidean space;then, we apply semi-supervised learning techniques to classify unannotated proteins into different functional groups. Finally, we made predictions to the unknown functional proteins in yeast. 5-fold cross validation is then applied to the GO terms to compare the performance of different approaches, and the proposed method performs significantly better than the others.

关键词： Bioinformatics Semisupervised learning Genomics Protein sequence Gene expression Learning systems Sun intelligent networks intelligent structures Computer networks

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Numerical Simulation of GPR based on 3-D High-order FDTD

Numerical Simulation of GPR based on 3-D High-order FDTD

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第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

作者： Zhi-xiang Huang Hong-mei Du Yi-cai Mei Xin-gang Ren Xian-liang Wu Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Department of Physics and Electronic Engineering Hefei Normal University Hefei China

The high-order finite-difference time-domain (HO-FDTD) technique is used in the simulation of ground-penetrating radar modeling in three dimensions (3-D), which can improve accuracy and reduce the error caused by numerical dispersion effectively. To absorb waves reflected from edges we implement convolutional perfectly matched layer (CPML) absorbing boundaries. It can efficiently absorb the reflections and greatly increase the computation efficiency. The surface-based reflection and cross-hole GPR modeling are simulated, and numerical results show the efficiency of the method.

关键词： Materials

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Teaching Reform and Innovation of the Course - Digital Image processing Experiments

Teaching Reform and Innovation of the Course - Digital Image...

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The 5th International Conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Haifeng Zhao Jin Tang Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230039P. R. China

Digital image processing is an interdisciplinary course, which needs students have a strong background in mathematics. To help them change from passive learning to active learning, teaching reform and innovation of the course "Digital Image processing Experiments" is discussed in this paper. The combined platform of experiments includes TI DSP experimental box and three different kinds of programming languages. The six experimental projects cover the basic theories of digital image processing. The result can offer a significant reference for the teaching innovations in the other related specialties.

关键词： digital image processing:experimental teaching matlab:DSP

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Si-Bao Chen Hai-Xian Wang Bin Luo Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui China Key Lab of Child Development and Learning Science of Ministry of Education Research Center of Learning Sciences South-East University Nanjing Jiangsu China

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD.

关键词： Harmonic analysis Training Laplace equations Manifolds Covariance matrix Machine learning Symmetric matrices

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Shot Transition Detection Based on Locally Linear Embedding

Shot Transition Detection Based on Locally Linear Embedding

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2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

作者： MaoSheng Fu DaMing Zhang Min Kong Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei230039. P. R. China Department of Computer Science and Technology in West Anhui University Anhui Lu'an 237012. P. R. China

ISBN: (纸本)9781424450015

Detection of shot transitions servers as the preliminary step to video indexing and retrieval. Locally linear embedding (LLE) algorithm fails when it is applied to video with multi-shot. In this paper, we present a novel framework of shot transitions detection. The method involves two processes: First we extract the manifold feature of shot transition using LLE through addition of virtual frames on an enriched set, and then they are classified by *** show that the recognition rate of shot transition is reached over 90％.

关键词： shot transition detection locally linear embedding feature extraction

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A 5-Parameter bundld adjustment method for image mosaic

A 5-Parameter bundld adjustment method for image mosaic

引用

8th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2009

作者： Fang, Xianyong Luo, Bin Zhao, Haifeng Zhang, Yiwen Key Lab. of Intelligent Computing and Signal Processing of MOE School of Computer Science and Technology Anhui University China

ISBN: (纸本)9780769536415

A 5-parameter bundle adjustment method is proposed in this paper for global mosaic of an image sequence. By decomposing the rotation matrix into a 3-parameter rotation axis and a rotation angle, to each image, there are 5 parameters that need estimate for rotation axis, rotation angle and focal length. The proposed method minimizes the distance between feature matches in 3D space so that these 5 parameters are refined gradually for final stitching of all images together. Experimental results suggest that this method is an useful extension to existing research with the advantages of real 3D camera motion, accurate 5-parameter rotation decomposition and reliable 3D feature definition. © 2009 IEEE.

关键词： Rotation

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