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2014 AASRI International Conference on Applied Engineering Sciences（ICAES2014）

作者： M.Peng M.Q.Li B.Rong Y.Ding Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University

In this paper,a novel design of the Wideband Bandstop Filter,based on Split Ring Resonators,(SRR) is *** Defect Ground Structure(DGS) is achieved by opening the SRR-shaped slot in the ground plane,and the metal cylinder is added between micro-strip line and the *** the above two methods,the wideband bandstop characteristics can be *** proposed structure is simulated by the high frequency simulation software HFSS 13.0,and the effect on the performance of a wideband Band-stop Filter by adding a metal column is *** design of Band-stop Filter structure with three cascaded SRR-shaped DGS units is *** the simulated and measured results show that the attenuation at the resonance frequency center reaches- 55 dB,and its relative bandwidth less than-10 dB is extended to 42% ranging from 5.6 GHz to 8.6 ***,the insertion loss of passband is limited to 1.2 dB.

关键词： A novel wideband band-stop filter based on SRR DGS Filter SRR

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Robust Spatial Filters on Three-Class Motor Imagery EEG Data Using Independent Component Analysis

Robust Spatial Filters on Three-Class Motor Imagery EEG Data...

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2014春季国际工程与技术大会

作者： Bangyan Zhou Xiaopei Wu Lei Zhang Zhao Lv Xiaojing Guo The Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University

Independent Component Analysis(ICA) was often used to separate movement related indepen-dent components(MRICs) from Electroencephalogram(EEG) data. However, to obtain robust spa-tial filters, complex characteristic features, which were manually selected in most cases, have been commonly used. This study proposed a new simple algorithm to extract MRICs automatically, which just utilized the spatial distribution pattern of ICs. The main goal of this study was to show the relationship between spatial filters performance and designing samples. The EEG data which contain mixed brain states(preparing, motor imagery and rest) were used to design spatial filters. Meanwhile, the single class data was also used to calculate spatial filters to assess whether the MRICs extracted on different class motor imagery spatial filters are similar. Furthermore, the spa-tial filters constructed on one subject's EEG data were applied to extract the others' MRICs. Finally, the different spatial filters were then applied to single-trial EEG to extract MRICs, and Support Vector Machine(SVM) classifiers were used to discriminate left hand、right-hand and foot imagery movements of BCI Competition IV Dataset 2a, which recorded four motor imagery data of nine subjects. The results suggested that any segment of finite motor imagery EEG samples could be used to design ICA spatial filters, and the extracted MRICs are consistent if the position of elec-trodes are the same, which confirmed the robustness and practicality of ICA used in the motor imagery Brain Computer Interfaces(MI-BCI) systems.

关键词： ICA Spatial Filter Motor Imagery BCI SVM

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Spectral clustering based on the edge betweenness dissimilarity matrix for community detection

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Journal of Information and Computational Science 2014年第11期11卷 3929-3939页

作者： Pei, Tingrui Cao, Yuxin Li, Zhetao Choi, Young-June College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

As an important global geometric quantity, edge betweennesses can reflect the impact of corresponding edges in the entire network, which have a very strong practical significance. However, edge betweenness ignores the relationship between the vertices which connected indirectly with the edge. This paper first puts forward a dissimilarity matrix based on a novel edge betweenness, and applies it to a spectral clustering algorithm and finally, in order to detect the community structure in complex networks with this improved algorithm, we use a correction step which is based on the gravitation force of the community. This algorithm has been tested on computer-generated networks and typical real world networks. Compared to GN, PBD, GK and DA, the proposed algorithm possesses an apparent advantage. ©2014 Binary Information Press

关键词： Complex networks

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Dense Invariant Feature Based Support Vector Ranking for Person Re-identification

Dense Invariant Feature Based Support Vector Ranking for Per...

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IEEE Global Conference on signal and Information processing

作者： Shoubiao Tan Feng Zheng Ling Shao Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 China Department of Electronic and Electrical Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK Department of Computer Science and Digital Technologies Northumbria University Newcastle upon Tyne NE1 8ST UK

ISBN: (纸本)9781479975921

Recently, support vector ranking has been adopted to address the challenging person re-identification problem. However, the ranking model based on ordinary global features cannot represent the significant variation of pose and viewpoint across camera views. Thus, a novel ranking method which fuses the dense invariant features is proposed in this paper to model the variation of images across camera views. By maximizing the margin and minimizing the error score for the fused features, an optimal space for ranking has been learned. Due to the invariance of the dense invariant features and the fusion of the bidirectional features, the proposed method significantly outperforms the original support vector ranking algorithm and is competitive with state-of-the-art techniques on two challenging datasets, showing its potential for real-world person re-identification.

关键词： Person Re-identification Dense Invariant Feature Support Vector Ranking Feature Fusion

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A hybrid artificial fish-school optimization algorithm for solving the quadratic assignment problem 10

A hybrid artificial fish-school optimization algorithm for s...

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2014 10th International Conference on Natural Computation, ICNC 2014

作者： Ziqiang, Li Yi, Yang Yang, Qiwei School of Information and Engineering Xiangtan University Xiangtan411105 China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan411105 China

ISBN: (纸本)9781479951505

The quadratic assignment problem (QAP) is a classic combinatorial optimization problem, which is of the NP-hard nature. In this paper, a hybrid artificial fish school optimization algorithm (HAFSOA) is proposed. In HAFSOA, the heuristic information is used in constructing some better initial individuals and its search ability of the global optimal solution is improved by a combination of the modified fish school optimization and differential evolution. In addition, by taking different visual distances for three behaviors: preying, clustering and following, the convergence speed of the proposed HAFSOA is speeded up. Many QAP experimental results show that the proposed HAFSOA can solve QAP better. © 2014 IEEE.

关键词： Evolutionary algorithms

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Secondary structure element alignment kernel method for prediction of protein structural classes

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Current Bioinformatics 2014年第3期9卷 253-257页

作者： Han, Guo-Sheng Yu, Zu-Guo Anh, Vo Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q 4001 Australia

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α+ β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://***/myphp/math/research/source/SSEAK_source_***. © 2014 Bentham Science Publishers.

关键词： Support vector machines

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Survey of community structure segmentation in complex networks

Journal of Software

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Journal of Software 2014年第1期9卷 89-93页

作者： Pei, Tingrui Zhang, Hongzhi Li, Zhetao Choi, Youngjune College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

Community structure analysis is a hot research spot in social networks and complex networks. In order to summarize recent research progress, this paper reviews the background, the motivation, the advantages and disadvantages of existing works related to community structure discovering. A comprehensive outline was obtained by analysis of different clustering algorithms. © 2014 ACADEMY PUBLISHER.

关键词： Complex networks

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Identity Recognition of Multi-Haptic Pressure Feature based on Sparse Representation

Identity Recognition of Multi-Haptic Pressure Feature based ...

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The 6th International Conference on Computer Research and Development

作者： Yan Zhang Dong Liang Ming Zhu Wenxia Bao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Physics and Materials ScienceAnhui University School of Electronics and Information Engineering Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education

Herein,a new identity recognition method of multi-haptic pressure feature based on sparse representation was *** to the common dynamic features,the regional feature and the ratio of length *** of external bounding rectangle(extracted by using the least area method) were *** subset of dynamic feature was optimized by correlation criterion,the sparse representation of haptic pressure was obtained according to the sparse basis(i.e.,wavelet basis),and the sparse feature vector was calculated by the Topelitz measurement *** that,the haptic pressure feature set was created by combining dynamic feature subset and sparse feature subset ***,Support Vector Machine(SVM) classifier identified more than two objects following the one to many rule and output the identification result according to the rule of majority voting,and the stability of features is studied by calculating the intraclass correlation coefficient(ICC) and coefficient of variation(C.V).Overall,the improved acuracy of identity recognition demonstrating the effectiveness and stability of the multihaptic pressure feature.

关键词： dynamic feature sparse representation optimization correlation criterion recognition

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Color analysis of iron surface structure fabricated by circularly polarized femtosecond laser

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Guangxue Jingmi Gongcheng/Optics and Precision Engineering 2015年 23卷 52-56页

作者： Su, Ya-Hui Han, Xiao-Hu Fan, Zhen-Zhu Zhang, Hua-Yong Zhong, Hong-Mei School of Electrical Engineering and Automation Anhui University Hefei230601 China School of Electrical and Information Engineering Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Anhui University Hefei230039 China

A method to induce multi-colors on an iron surface by using Circularly Polarized Femtosecond Laser (CPFL) processing was proposed. The subwavelength ripples were fabricated by CPFL scanning over the iron surface where covered by randomly distributed nanoparticles with diameters from 50 nm to 190 nm. A while light was used to irradiate the treated iron surface, and the relation between surface colors and incident angles was explored. By changing the incident angles of a white light from 0° to 80°, diverse colors were displayed on the laser-treated iron surface. In order to understand the underlying mechanism of the experimental results, a model of spherical nanoparticles spread randomly on ripples of the iron surface was built by Finite-difference Time Domain (FDTD). The experiments show that the surface reflection spectrum is varied from blue to red by increasing the incident angle of white light, which is consistent with the experimental results. Furthermore, it is found that the reflection spectrum shifts towards blue and the peak increases by decreasing the sizes of nanoparticles. This work may find potential applications in the fields of information storage, identifying codes and anti-counterfeiting patterns. © 2015, Chinese Academy of Sciences. All right reserved.

关键词： Femtosecond lasers

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CM-curve: A 2D graphical representation of protein sequences and its application

CM-curve: A 2D graphical representation of protein sequences...

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2014 International Conference on Medical Engineering and Bioinformatics, MEB 2014

作者： Wang, Lei Peng, Hui Zheng, Jinhua Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan University Xiangtan China College of Information Engineering Xiangtan University Xiangtan China

ISBN: (纸本)9781845649920

To facilitate the intuitional analysis of the protein sequences, we introduce a novel 2D graphical representation method CM-curve based on the characteristic model of protein sequence, which may reflect the innate structure of the protein sequence. And then, we design two numerical characterizations of protein graphs as descriptors to analyze the similarity/dissimilarity of the nine ND5 protein sequences. Comparing with existing methods, our method is not only proved to be visible, intuitional, and simple but also has no circuit or degeneracy, and even more important, it can keep excellent visual inspection for long protein sequence because the storage space required by our method is constant and has nothing to do with the length of protein sequence. © 2014 WIT Press.

关键词： Proteins

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