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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Zhang, Yanping Yu, Jiajia He, Fugui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9780769542867

Community structure is an important common property of complex network which has much theoretical significance for analyzing structure, mastering function, detecting implicit scheme and predicting activities. This paper reviews some popular detecting community methods. NTCDC Algorithm is proposed by analyzing weigh of nodes' and edges' TC values. The algorithm not only improves the precision, but also faster than GN and fast algorithm proposed by Newman. This paper demonstrate that the algorithm is higher effective and faster at discovering community structure in both computer-generated network and real-world network data than GN and fast algorithm. © 2010 IEEE.

关键词： Complex networks

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Face recognition using fuzzy rough set and support vector machine

Face recognition using fuzzy rough set and support vector ma...

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2010 IEEE International Conference on intelligent computing and intelligent Systems, ICIS 2010

作者： Wang, Shi-Yi Tao, Liang MOE Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Computer Department Chaohu College Chaohu 238000 China

ISBN: (纸本)9781424465835

This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet decomposition technique with the grayscale integral projection technique. And then, the attribute reduction algorithm based on FRST is applied in face recognition. The reduction algorithm based on FRST can eliminate the redundant features of sample dataset and reduce the space dimension of the sample data. The proposed method avoids losing of information caused by dispersing before original rough set attribute reduction. Experimental results show that it can improve the classification accuracy in face recognition as compared with the method using the original rough set. ©2010 IEEE.

关键词： Face recognition

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The classification of gene expression profile based on the adjacency matrix spectral decomposition

The classification of gene expression profile based on the a...

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International Conference on Computer Application and System Modeling

作者： Su, Liangliang Wang, Nian Tang, Jun Chen, Le Wang, Ruiping Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9781424472369

In the process of disease diagnosis, determining the types of disease is very important. With the development of DNA microarray technology, the research on huge gene expression profile has become the focus of disease classification. This paper presents a method of classification of gene expression profile based on the adjacency matrix spectral decomposition. First, samples are mapped to a high-dimensional space of points to construct an adjacency matrix, and we can obtain eigenvectors describing the feature of the samples by decomposing the matrix. Finally, use eigenvectors as inputs of the SVM (Support Vector Machine) and KNN (K nearest neighbor) classifiers to classify gene expression profile. In this way sample information can be completely preserved, which enables an approach to making gene expression profile from one without structural information to one with structural information. The validity of this method is verified by comparative experiments. © 2010 IEEE.

关键词： Eigenvalues and eigenfunctions

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Motor imagery classification based on the optimized SVM and BPNN by GA

Motor imagery classification based on the optimized SVM and ...

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2010 International Conference on intelligent Control and Information processing, ICICIP 2010

作者： Jiao, Yingying Wu, Xiaopei Guo, Xiaojing Key Laboratory of Intelligent Computing and Signal Processing of MOE Anhui University Hefei 230039 Anhui Province China School of Computer Science and Technology Anhui University China

ISBN: (纸本)9781424470488

Brain-computer interface (BCI) is a specific Human-Computer interface in which the brain wave is employed as the carrier of control information. The ultimate goal of BCI is to build a direct communication pathway between human brain and external environment that does not depend on the limb mobility and language. In this paper, we carry out the experiment about the left or right hand motor imagery, and support vector machine with genetic algorithm(GA-SVM) and back propagation neural network with genetic algorithm (GA-BP) are employed to classify the μ. rhythm evoked by movement imagination. The experiment results prove that GA-SVM can easily find out the appropriate parameters of SVM and GA-BP can avoid getting into local minimization to great extend. So higher accuracy of classification is achieved. © 2010 IEEE.

关键词： Brain computer interface

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Locating human eyes in face images based on illumination normalization and progressive thresholding

Locating human eyes in face images based on illumination nor...

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International Conference on Computer Science and Education

作者： Wang, Hua-Bin Tao, Liang Hu, Xue-You Wang, Shi-Yi Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9781424460052

Based on illumination normalization and progressive thresholding, this paper presents a novel algorithm for automatic localization of human eyes in still images with complex background. First of all, Retinex method is used to realize normalizing of the face image. Secondly, a determination criterion of eye location is established by the priori knowledge of geometrical facial features. Thirdly, a range of threshold values that would separate eye blocks from others in a segmented face image is estimated. With the progressive increase of the threshold by an appropriate step in that range, once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. The experimental results demonstrate the high efficiency of the algorithm in runtime and correct localization rate. ©2010 IEEE.

关键词： Image segmentation

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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, ICITIS 2010

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

ISBN: (纸本)9781424469406

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 zero-knowledge 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. © 2010 IEEE.

关键词： Ad hoc networks

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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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An improved target immunization strategy

An improved target immunization strategy

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Zhang, Yanping Fang, Baoping Deng, Xiaochao He, Fugui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Key Laboratory of Physical Electronics of Anhui University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9780769542867

Strategies for network immunization have been drawing wide interest in the area of complex networks during the past decade. The target strategy, in which degree values are used to determine vaccinating priority, has been supposed to be the most effective strategy. In many networks where large numbers of nodes exists with same degree values, the target strategy will face a problem of deciding the priorities of nodes with equal degree. This paper discussed a refined method to evaluate priority using risk-value. With risk-values, an improved target immunization strategy is proposed. Simulations under SIS model using real network dataset have proved a better efficiency for the improved strategy. © 2010 IEEE.

关键词： Complex networks

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Block wavelet transforms of image reconstruction using compressed sampling

Block wavelet transforms of image reconstruction using compr...

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International Congress on Image and signal processing

作者： Zhang, Liang Wu, Xian-Liang Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China Department of Physics and Electronic Engineering Hefei Teachers College Hefei 230061 China

ISBN: (纸本)9781424465149

This paper describes the compressed sampling using the block wavelet transform which has more flexibility in reconstruction the images. Compressed sampling is considered for signals and images that are sparse in a wavelet basis. We propose a process of the image by sampling the data far below Nyquist rate in terms of compressed sampling, which shows that image data can be reconstructed from an extremely small set of measurements than what is generally considered necessary. A novel wavelet based interframe compression scheme has been developed and put into practice. It is based on a unique block wavelet transform that we have developed. BWT based interframe compression is very efficient in both compression and speed performance. The compression performance of our image codec hold a slightly lower PSNR value produces a more visually pleasing result. This implementation also preserves the scalability of the wavelet embedded coding technique. ©2010 IEEE.

关键词： Wavelet transforms

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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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