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IEEE International Conference on Granular computing (GRC)

作者： Hongbin Fang Ling Zhang Department of Mathematics Anhui University Hefei China Department of Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Institute of Artificial Intelligence Anhui University Hefei China

The quotient space theory obtains a fusion model about semi-order structure under the condition of consistency information, harnessing topology relation among elements of the universe space and hierarchical structure. It has great significance to forming a unified theory structure about information fusion technology. This paper gets a new semi-order structure fusion model under the condition of inconsistency information and proves incompleteness of its semi-order lattice . An example is presented in the paper at last as well as a new method is indicated for Bayesian network structure learning.

关键词： Space technology Laboratories signal processing Lattices Bayesian methods Network topology Fuzzy set theory Entropy Cognition Concrete

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A note on equicontinuous maps of graph space

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Journal of Chongqing University 2005年第2期4卷 121-124页

作者：乔宗敏 Key Laboratory of intelligent Computing and Signal Processing of Ministry of Education Anhui UniversityHefei 230039 P.R. China Department of Mathematics Anhui Educational Institute Hefei 230061 P.R. China

Let G be a graph and f: G→ G be a continuous map with at least one periodic point. Using the quote space method, the paper addresses that f is an equicontinuous map if and only if one of the following End(G)+2k+1 conditions holds: 1) {f jm(End(G)+2k)!}∞j=1 is uniformly convergent, in which m=1,2,…, End(G)+2k; and 2) There is a positive integer n esuring that {f jn}∞j=1 is uniformly convergent.

关键词： graph equcontinuous map quotient space uniformly convergent

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Greedy EM algorithm for robust t-mixture modeling

Greedy EM algorithm for robust t-mixture modeling

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International Conference on Image and Graphics (ICIG)

作者： Sibao Chen Haixian Wang Bin Luo Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to determine how to insert new component. The greedy algorithm obviates the complicated initialization. The results are comparable to that of split-and-merge EM algorithm while the proposed algorithm is faster. Also the by product of a sequence of mixture models is useful for model selection. Experiments of synthetic data clustering and unsupervised color image segmentation are given.

关键词： Robustness signal processing algorithms Clustering algorithms Tail Greedy algorithms Convergence Gaussian distribution Color Image segmentation Probability distribution

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Robust t-mixture modelling with SMEM algorithm

Robust t-mixture modelling with SMEM algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Si-Bao Chen Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University of Science and Technology Hefei China

ISBN: (纸本)0780384032

Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the problem of local convergence of the traditional EM algorithm, a split-and-merge operation is introduced into the EM algorithm for multivariate t-mixtures. The split-and-merge equations are first presented theoretically and then a new merge method is acquired. Accordingly, a modified EM algorithm is constructed. Experiments of data clustering and unsupervised color image segmentation are given.

关键词： Robustness Clustering algorithms signal processing algorithms Image segmentation Parameter estimation Gaussian distribution Probability density function Covariance matrix Tail Equations

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Mental EEG analysis based on independent component analysis

Mental EEG analysis based on independent component analysis

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International Symposium on Image and signal processing and Analysis

作者： Xiaopei Wu Xiaojing Guo The Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University China

ISBN: (纸本)953184061X

The patterns of EEG changes with the mental tasks performed by the subject. In the field of EEG signal analysis and application, the study to get the patterns of mental EEG and then to use them to classify mental tasks has the significant scientific meaning and great application value. But for the reasons of different artifacts contained in EEG, the pattern detection in EEG produced from normal mental states is a very difficult problem. In this paper, independent component analysis is applied to EEG signals collected from different mental tasks .The experiment results show that when one subject performs a single mental task in different trails, the independent components of EEG are very similar. It means that the independent components can be used as the mental EEG patterns to classify the different mental tasks.

关键词： Independent component analysis Electroencephalography signal processing signal processing algorithms Bioelectric phenomena Biomedical signal processing signal analysis Humans Electric potential Brain modeling

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A new algorithm for 3D projective reconstruction based on infinite homography

A new algorithm for 3D projective reconstruction based on in...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Quan-Bing Zhang Hai-Xian Wang Sui Wei Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (纸本)0780378652

This paper investigates the problem of how to carry out 3D scene reconstruction from multiple views. It improves the algorithms of projective reconstruction based on the homography induced by the infinite plane which should have 4 points on a reference plane visible in all views given by Hartley and Rother et al., and proposes a new linear algorithm based on 3 points on a reference plane visible in all views. It avoids the difficult task of determining whether 4 object points are coplanar or not, because 3 points which are not collinear just determine a plane.

关键词： Image reconstruction Cameras signal processing algorithms Layout Transmission line matrix methods Inverse problems Gold Measurement standards Maximum likelihood estimation Position measurement

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A self-adjusting and probabilistic decision-making classifier based on the constructive covering algorithm in neural networks

A self-adjusting and probabilistic decision-making classifie...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yan-Ping Zhang Tao Wu Ling Zhang Ministry of Education Key Laboratory of Intelligent computing & Signal Processing Anhui University Hefei China

ISBN: (纸本)0780375084

It usually needs complicated nonlinear operations to get the characteristics from the raw information inputted, and it is very difficult to find this kind of algorithm directly. The geometrical meaning of the multilayer perceptron's neuron model indicates that classifying samples according to the requirements by constructing neural networks is equal to finding a collection of domains with which vectors of the preset sample sets are partitioned. But in some applications, such as time series forecasting including stock share forecasting, due to their preset sample sets may contain some exceptions and erroneous results, it is desired to introduce some self-adjusting and probabilistic decision-making mechanism to enhance the accuracy of classification. At the same time the mechanism can reduce the size of neural networks and speed up the recognition process. We discuss a self-adjusting and probabilistic decision-making mechanism for the covering algorithm. Based on the method, we developed a self-adjusting and probabilistic decision-making classifier and applied the software package to forecast the share index of Shanghai's stock market.

关键词： Decision making intelligent networks Neural networks signal processing algorithms Support vector machines Neurons Solid modeling Stock markets Kernel Economic forecasting

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Panoramic mosaicing with image interpolation

Panoramic mosaicing with image interpolation

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2001 International Symposium on intelligent Multimedia, Video and Speech processing, ISIMP 2001

作者： Ruan, Zong-Cai Liang, Dong Wei, Sui Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9628576623

Panoramic mosaics methods based on 8-paramter planar homography matrix have to overcome the accumulated errors, when a sequence of images loops back on itself. Usual methods are computationally intensive, and can not ensure complete consistency of homographies. This paper presents a simple method, which do not require the consistency of homographies. The method mainly exploits un-calibrated image perspective interpolation technique [1]. So it is of simple calculation and easy realization.

关键词： Interpolation

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Panoramic mosaicing with image interpolation

Panoramic mosaicing with image interpolation

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International Symposium on intelligent Multimedia, Video and Speech processing

作者： Zong-Cai Ruan Dong Liang Sui Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University of Science and Technology Hefei China

ISBN: (纸本)9628576623

Panoramic mosaics methods based on an 8-parameter planar homography matrix have to overcome the accumulated errors when a sequence of images loops back on itself. Usual methods are computationally intensive, and cannot ensure complete consistency of homographies. The paper presents a simple method which does not require the consistency of homographies. The method mainly exploits an un-calibrated image perspective interpolation technique (B. Yuan et al., 1998). It is therefore simple to calculate and easy to implement.

关键词： Interpolation Transmission line matrix methods Matrix decomposition Equations Error correction Computational intelligence signal processing Nonlinear optics Optical signal processing Image motion analysis

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An indirect convergent Jacobi spectral collocation method for fractional optimal control problems

An indirect convergent Jacobi spectral collocation method fo...

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作者： Yang, Yin Zhang, Jiaqi Liu, Huan O. Vasilev, Aleksandr Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Xiangtan Hunan China Ammosov North-Eastern Federal University Yakutsk Russia

In this paper, we present a novel indirect convergent Jacobi spectral collocation method for fractional optimal control problems governed by a dynamical system including both classical derivative and Caputo fractional derivative. First, we present some necessary optimality conditions. Then we suggest a new Jacobi spectral collocation method to discretize the obtained conditions. By the proposed method, we get a system of algebraic equations by solving of which we can approximate the optimal solution of the main problem. Finally, we present a convergence analysis for our method and solve three numerical examples to show the efficiency and capability of the method. © 2019 John Wiley & Sons, Ltd.

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