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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

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. ©2010 IEEE.

关键词： Discriminant analysis

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GPU-Based Accelerated FDTD Simulations for Double Negative (DNG) Materials Applications

GPU-Based Accelerated FDTD Simulations for Double Negative (...

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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： Shen Chen Sun Dong Wu Xian-liang Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei 230039 china

Recently, double-negative meta-materials are widely studied in scientific research. The double-negative (DNG) mediums are characterized by simultaneous negative permittivity and permeability. In order to make the FDTD method analyze the electromagnetic scattering and propagation for double-negative (DNG) medium, z-transform is applied to the FDTD method in the double-negative (DNG) medium. For the simulations, extremely large computer memory space and a long computational time b required. A parallel algorithm for the FDTD method on the state of the art graphics hardware is presented. The parallel computing techniques can be used to reduce the computation time significantly and have been widely applied in various complex FDTD applications. In this paper, we simulate the interaction between electromagnetic wave and DNG medium, and describe an impact of new GPU features on development process of an efficient Finite Difference Time Domain (FDTD) implementation.

关键词： Acceleration Finite difference methods Time domain analysis Electromagnetic scattering Computational modeling Permittivity Permeability Electromagnetic analysis Electromagnetic propagation Computer simulation

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Image denoising based on non-local means and multi-scale dyadic wavelet transform

Image denoising based on non-local means and multi-scale dya...

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2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010

作者： Yu, Gang Yin, Yong Wang, Hongjun Liu, Zhi Li, Oengwang School of Information Science and Engineering Shandong University Jinan China Department of Radiation Oncology Shandong Tumor Hospital China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan China

ISBN: (纸本)9781424455386

A variety of wavelet transform methods have been introduced to remove noise from images. However, many of these algorithms remove the fine details and smooth the structures of the image when removing noise. The wavelet coefficient magnitude sum (WCMS) algorithm can preserve edges, but it is at the expense of removing noise. The Non-Local means algorithm can removing noise effective. But it tend to cause distortion (eg white). Meanwhile, when the noise is large, the method is not so effective. In this paper, we propose an efficient denoising algorithm. we denoised the image with non-local means algorithm in the spatial domain and WCMS algorithm in wavelet domain, weithted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6dB to 1.0dB and the image boundary is more clearly. © 2010 IEEE.

关键词： Wavelet transforms

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A Secure Distributed key Management Scheme for AD Hoc Network

A Secure Distributed Key Management Scheme for AD Hoc Networ...

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2010 IEEE International Conference on Information Theory and Information Security(2010 IEEE 国际信息论与信息安全会议)

作者： Xianping Yuan Yan Xu Hong Zhong Jia Yu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Univers College of Information Engineering Qingdao University Qingdao China

An identity-based threshold key management scheme without secure channel is proposed for ad hoc network. The master private key, which is shared among all nodes by the Shamir's secret sharing scheme, is produced by all nodes when network is formed. The nodes’ public keys are derived from their identities. In order to get the private key, each node needs to prove their identity to distributed CAs using a zeroknowledge proof protocol to get the share of private key. Compared with former schemes, our scheme doesn’t need any local registration authority(LRA), which is easy to be compromised by adversary. When a node leaves the network, shares of the master private key would be renewed. In the end, we prove our scheme is correct and secure.

关键词： Ad hoc networks Public key Polynomials Protocols Wireless communication

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Application of AWE to scattering analysis of the double-negative medium (RCS) within a wider band.

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

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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： Mei Yang Yu-Xin Sun Hui Wang Ming-Sheng Chen 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 School of In Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

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.

关键词： Moment methods Optical propagation Silicon compounds

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Efficient multi-resolution detection of binary object

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Information Technology Journal 2010年第8期9卷 1641-1646页

作者： Fang, Xianyong Wu, Hao MOE Key Laboratory of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Anhui 230039 China

This study presents an efficient multi-resolution method to detect binary object directly. Both intensity and geometry differences are used to measure the similarity between the source object template and target objects inside the test image. Especially for the geometrical difference, the histogram of oriented gradients is proposed to measure the similarity of the edge images between the source object template and the target object. Based on these two measurements, a multi-resolution strategy is used to accurately locate the object position in a coarse-to-fine way, where intensity difference and geometry difference applied consequently in each layer. Experimental results demonstrate the efficiency of the proposed method. © 2010 Asian Network for Scientific Information.

关键词： Geometry

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Compressive Sensing for Wide-Angle Analysis

Compressive Sensing for Wide-Angle Analysis

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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： Hong-Mei Du Yi-Cai Mei Si-Long Lu Ming-Sheng Chen 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 230601 China Schoo Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

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.

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On dynamic weighting of data in clustering with K-alpha means

On dynamic weighting of data in clustering with K-alpha mean...

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab. of Child Development and Learning Science Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9780769541099

Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which deemphasizes data points that are close to centers while emphasizes data points that are not close to any centers. Through replacing minimum operator in K-Means by alpha-mean operator, KAM significantly improves the clustering performances. © 2010 IEEE.

关键词： Clustering algorithms

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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

关键词： Method of moments

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Motor Imagery EEG Classification based on Dynamic ICA Mixing Matrix

Motor Imagery EEG Classification based on Dynamic ICA Mixing...

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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： Xiaojing Guo Xiaopei Wu The Key Laboratory of Intelligent Computing & Signal Processing of MOE Anhui University Hefei city Anhui province China

Recently the mu rhythm by motor imagination has been used as a reliable EEG pattern for brain-computer interface (BCI) system. To motor-imagery-based BCI, feature extraction and classification are two critical stages. This paper explores a dynamic ICA base on sliding window Infomax algorithm to analyze motor imagery EEG. The method can get a dynamic mixing matrix with the new data inputting, which is unlike the static mixing matrix in traditional ICA algorithm. And by using the feature patterns based on total energy of dynamic mixing matrix coefficients in a certain time window, the classification accuracy without training can be achieved beyond 85% for BCI competition 2003 data set Ⅲ. The results demonstrate that the method can be used for the extraction and classification of motor imagery EEG. In the present study, it suggests that the proposed algorithm may provide a valuable alternative to study motor imagery EEG for BCI applications.

关键词： Electroencephalography Independent component analysis signal processing algorithms Brain computer interfaces Computer interfaces Rhythm Laboratories signal processing Cities and towns Feature extraction

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