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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Xiaopei Wu Zhongfu Ye School of Information Science and Technology University of Science and Technology Hefei Anhui China The Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei Anhui China

An online infomax algorithm is proposed in this paper. The performances and properties of this online algorithm is investigated in detail. To the problem of the artifacts removal in real life EEG signal, both the online-and batch infomax algorithm are applied and compared. The experiment results show that the online infomax algorithm proposed in this paper has the good performance both in artifacts removal and convergence in time-varying mixing system

关键词： Electroencephalography signal processing algorithms Independent component analysis Equations Electrocardiography Gaussian processes World Wide Web Biology computing Biomedical engineering Biomedical signal processing

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Bayesian-based Wavelet Shrinkage for SAR Image Despeckling Using Cycle Spinning

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Journal of Electronic Science and Technology of China 2006年第2期4卷 127-131页

作者：张德祥高清维陈军宁 Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Electronic Science and Technology Anhui University Hefei 230039 China

A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed （MGD） modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeclding algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.

关键词： discrete wavelet transform Synthetic Aperture Radar （SAR） despeclding cycle spinning BayesShrink

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Quotient space approachability basing on measure space and fusion model of weighted graphical structure

Quotient space approachability basing on measure space and f...

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IEEE International Conference on Granular computing (GRC)

作者： HongBin Fang Ling Zhang Department of Mathmatics Anhui University Hefei China Department of Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Institute of Artifical Intelligence Anhui University Hefei China

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Content-based 3-D Shape Retrieval for Pervasive computing

Content-based 3-D Shape Retrieval for Pervasive Computing

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International Conference on Pervasive computing and Applications (ICPCA)

作者： Dong Xu Hua Li Zongkai Lin Chinese Academy of Sciences China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Science National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Science. lihua@*** Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China

3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment

关键词： Shape Content based retrieval Pervasive computing Information retrieval Humans Internet Application software Laboratories intelligent networks Computer networks

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A Novel Approch for Clustering of Chinese Text Based on Concept Hierarchy

A Novel Approch for Clustering of Chinese Text Based on Conc...

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IEEE International Conference on Cognitive Informatics

作者： Peng Zhao Huan-Tong Geng Qing-Sheng Cai University of Science and Technology Hefei China Key Lab. Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic classify dictionary as background knowledge to clustering of Chinese text. It adopts a hierarchical coding system which reflects concept relevance among different words and uses vector space model based on concept hierarchy to represent Chinese text. The experimental results show this approach is more effective than traditional text clustering method based on keywords set

关键词： Dictionaries Space technology Clustering methods Documentation Text mining Clustering algorithms Frequency Computer science signal processing signal analysis

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Strong Convergence of Empirical Distribution for a Class of Random Matrices

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Chinese Quarterly Journal of Mathematics 2006年第1期21卷 28-32页

作者： LIANG Qing-wen MIAO Bai-qi WANG Da-peng Department of Statistics and Finance University of Science and Technology of China Hefei 230026 China Key Lab of intelligent Computing and Signal Processing of the Ministry of Education AnhuiUniversity Hefei 230026 China

Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai×si and si=1/√N（v1i,…, vN,i）^T. The spectral distribution of SN is proven to converge, with probability one, to a nonrandom distribution function under mild conditions.

关键词： empirical spectral distribution function sample covariance matrix Stieltjes transform strong convergence

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Automatic Recognition of Noisy Code-39 Barcode

Automatic Recognition of Noisy Code-39 Barcode

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International Conference on Artificial Reality and Telexistence (ICAT)

作者： Xianyong Fang Fuli Wu Bin Luo Haifeng Zhao Peng Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China College of Information Engineering Zhejiang University of Technology China Motorola China Electronics Limited Corporation China

Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the first step, all asterisks in the image are found with evenly defined scan lines and then those with the same directions are matched together to get a valid barcode region. In the second step, a local denoise method is first applied to eliminate noise in the barcode region and then a middle band filter is used to decode the barcode. Our method is simple in comparison with former methods and experimental results show that it is efficient for fast barcode recognition on noisy images.

关键词： Decoding Bars Image edge detection Robustness Equations Low pass filters signal processing Educational institutions Educational technology Image recognition

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Granular Analysis of Time Sequence Based on Quotient Space

Granular Analysis of Time Sequence Based on Quotient Space

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on intelligent Agents, Web Technologies and Internet Commerce

作者： Liquan Zhao Ling Zhang Bo Zhang Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing China Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China Computer Science Department Tsinghua University Beijing China

This paper aims to carry out granular analysis of time sequence based on quotient space. Granular methods have long before been adopted to analyze time sequence, but the granularity was based on time, for example, day mean, month mean, year mean and so on in finance forecast. In this paper, the granularity is based on space and some significant results are obtained: we can, in certain circumstances, get characteristics of time sequence in an original space when carrying out granular analysis of it in its coarser-grain space; granular analysis of a Markov chain is equivalent to an hidden Markov model (HMM), contrarily, any HMM is equivalent to granular analysis of a Markov chain. These results deepened our understanding of HMM from the perspective of granular analysis. We can not only use the methods of HMM to study time sequence, but also use the methods of granular analysis based on quotient space theory to solve the problems of HMM.

关键词： Hidden Markov models Laboratories Artificial intelligence signal analysis Finance signal processing Computer science education Space technology Computational intelligence Economic forecasting

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A Global Geometric Approach for Image Clustering

A Global Geometric Approach for Image Clustering

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International Conference on Pattern Recognition

作者： Sulan Zhang Chunqi Shi Zhiyong Zhang Zhongzhi Shi Chinese Academy of Sciences China Institute of Computing Technology Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China

ISBN: (纸本)0769525210

We propose an appearance-based image clustering approach called GGCI (global geometric clustering for image). For face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images under different viewing conditions, GGCI uses easily measured local metric information to learn the underlying global geometry of images space, then apply the extended nearest neighbor approach to cluster images. Different from the usual nearest neighbor approach, GGCI considers the density around the nearest points within clusters. Moreover, our approach clusters based on the geodesic distance measure instead of Euclidean distance measure, which better reflects the intrinsic geometric structure of manifold embedded in high dimensional image space. Experimental results suggest that the proposed GGCI approach achieves lower error rates in image clustering when manifolds are embedded in image space

关键词： Level measurement Nearest neighbor searches Feature extraction Geophysics computing Eyes Euclidean distance Photoreceptors Information processing Computers Information geometry

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APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

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Journal of Electronics(China) 2006年第1期23卷 81-84页

作者： Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling Institute of Graphics and Image Processing Xianyang Normal University Xianyang 712000 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Insititute of Intelligent Information Processing Xidian University Xi＇an 710071 China

The functional network was introduced by ***, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance.

关键词： Functional network Ridgelet Approximation

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