检索结果-内蒙古大学图书馆

Convergence of variational iteration method for second-order delay differential equations

Journal of Applied Mathematics 2013年第unknown期2013卷 634670-1-634670-9页

作者： Liu, Hongliang Xiao, Aiguo Su, Lihong Key Laboratory of Intelligent Computing and Information Processing Xiangtan University Ministry of Education Xiangtan Hunan 411105 China

This paper employs the variational iteration method to obtain analytical solutions of second-order delay differential equations. The corresponding convergence results are obtained, and an effective technique for choosing a reasonable Lagrange multiplier is designed in the solving process. Moreover, some illustrative examples are given to show the efficiency of this method. © 2013 Hongliang Liu et al.

关键词： differential employs variational Differentiation matrix iteration iterative methods Differential equations delay EMPLOYMENT Converge Differential

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Novel non-convex online algorithms for robust ranking

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Journal of Information and Computational Science 2013年第17期10卷 5743-5759页

作者： Cheng, Fan Wang, Xufa Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Computer Anhui University Hefei 230039 China School of Computer University of Science and Technology of China Hefei 230027 China

Recently increasing attention has been focused on learning to rank, which aims to learn a ranking function from a set of training data with relevance labels. Many of the ranking algorithms are based on the pairwise preference framework. However, one disadvantage of pairwise ranking is that it is sensitive to the outliers. To tackle the problem, in this paper, we propose two novel online algorithms based on non-convex Ramp Loss which can suppress the influence of outliers. The first one directly defines a new objective function based on Ramp Loss. Considering that the objective function is non-convex, we use the Concave-convex Procedure (CCCP) for convex approximation, then design an online algorithm based on Dual Coordinate Descend Method to learn the final ranking model. The second algorithm applies selective sampling technology in the training phase. It ignores the instances that lie in the flat region of the Ramp Loss in advance, before they are processed by the learner. Experimental results show that the algorithms we proposed have significant robustness to outliers and yield better generalization performance than the baseline rankers, and the results also prove that our algorithms have less computational running time for their less support vectors. © 2013 Binary Information Press.

关键词： Approximation algorithms

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Image bag generator based on bag of visual words

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Journal of Information and Computational Science 2013年第5期10卷 1453-1462页

作者： Zhao, Shu Xu, Chao Xu, Xiansheng Xu, Chenchu Zhang, Yanping Ye, Hong School of Computer Science and Technology Anhui University Hefei 230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China Insurance Office Anhui Provincial Hospital Hefei 230001 China

Multi-instance learning is a good tool to deal with the ambiguity of image in Content-based Image Retrieval (CBIR). According to some researchers' work, image bag generator which transforms an image into an instance bag plays an important role in applying multi-instance learning for CBIR. In this paper, the bag generator based on bag of visual words, named Vdbag, is proposed. First, it extracts local features of image from all images, and then it obtains a set of visual words called visual vocabulary by clustering local features where each local cluster's center is a visual word. Our work mainly includes (1) We introduce bag of visual words into image bag generator. (2) We give a reasonable description to express the instance in an image bag. We add the frequency of each visual word as the last dimension of this visual word to construct the corresponding instance. Experimental results with Corel image database show that the proposed method could achieve better precision than that of some existing bag generators. © 2013 Binary Information Press.

关键词： Content based retrieval

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Video Summarization by Robust Low-Rank Subspace Segmentation

Advances in Intelligent Systems and Computing

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Advances in intelligent Systems and computing 2013年 212卷 929-937页

作者： Tu, Zhengzheng Sun, Dengdi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China School of Computer Science and Technology Anhui University Hefei 230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei 230039 China

ISBN: (纸本)9783642375019

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Vectors

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Method for convergent projective non-negative matrix factorization

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Journal of Information and Computational Science 2013年第6期10卷 1847-1854页

作者： Hu, Lirui Wu, Jianguo Wang, Lei Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China School of Computer Science and Technology Nantong University Nantong 226019 China School of Computer Science and Technology Anhui University Hefei 230039 China

In order to solve the problem of algorithm convergence in Projective Non-negative Matrix Factorization (P-NMF), a method, called Convergent Projective Non-negative Matrix Factorization (CP-NMF), is proposed. In CP-NMF, an objective function of Frobenius norm is defined. The Taylor series expansion and the Newton iteration formula of solving root are used. An iterative algorithm for basis matrix is derived, and a proof of algorithm convergence is provided. Experimental results show that the convergence speed of the algorithm is higher, however it is affected by the initial value of the basis matrix;relative to Non-negative Matrix Factorization (NMF), the orthogonality and the sparseness of the basis matrix are better, however the reconstructed results of data show that the basis matrix is still approximately orthogonal;in face recognition, there is higher recognition accuracy. The method for CP-NMF is effective. Copyright © 2013 Binary Information Press.

关键词： Face recognition

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Application and method of feature extraction for approximate orthogonal non-negative matrix factorization

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Journal of Computational Information Systems 2013年第2期9卷 805-812页

作者： Hu, Lirui Wu, Jianguo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China School of Computer Science and Technology Nantong University Nantong 226019 China School of Computer Science and Technology Anhui University Hefei 230039 China

In order to get effectively feature vectors of samples, a method of feature extraction is proposed based on non-negative matrix factorization (NMF) with approximate orthogonal constraint. An objective function is defined to impose approximate orthogonal constraint, in addition to the non-negative constraint in the standard NMF. An algorithm of iterative update for basis matrix and weight matrix in non-negative matrix factorization is derived, and then computational method of feature vectors is gotten. A proof of the convergence of the algorithm is provided. Empirical results of handwritten character recognition show that there is high recognition accuracy if only the rank of the basis matrix is set correctly. The method of feature extraction is useful to get essential feature of sample, and is effective to recognition when the structures of the handwritten characters are obviously different. Copyright © 2013 Binary Information Press.

关键词： Feature extraction

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The improved disc theorems for the Schur complements of diagonally dominant matrices

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Journal of Inequalities and Applications 2013年第1期2013卷 1-16页

作者： Zhang, Juan Liu, Jianzhou Tu, Gen Department of Mathematics and Computational Science Xiangtan University Xiangtan P.R. China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan P.R. China

The theory of Schur complement is very important in many fields such as control theory and computational mathematics. In this paper, applying the properties of Schur complement, utilizing some inequality techniques, some new estimates of diagonally dominant degree on the Schur complement of matrices are obtained, which improve some relative results. Further, as an application of these derived results, we present some distributions for the eigenvalues of the Schur complements. Finally, the numerical example is given to show the advantages of our derived results. MSC:15A45, 15A48.

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CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MULTI-ANGULAR HYPERSPECTRAL MEASUREMENTS

CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MUL...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jinling Zhao Lin Yuan Linsheng Huang Dongyan Zhang Jingcheng Zhang Xiaohe Gu Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9781479911127

This study aims at characterizing wheat canopies caused by powdery mildew (Blumeria graminis f. sp. tritici) with multi-angular hyperspectral data. The filling stage (23 May, 2012) was chosen to achieve such a goal, considering that the disease can show distinctive symptoms during the months of May and June. A total of 37 sample plots were selected including 32 normal canopies and 5 diseased canopies with varied severity. To minimizing the soil background influences, multi-angular hyperspectral data were acquired at different view angles (0°, 45° and 90°). The results showed that the proportion of wheat vegetation and soil changed greatly and the hyperspectral reflectance values correspondingly changed. Consequently, the reflectance at different viewing angles showed great differences, but the curves had the same change trends. The results showed that, to accurately identify the spectral differences caused by powdery mildew, the optimal angle or a combination of several angles must be firstly found from multi-angular hyperspectral measurements.

关键词： Hyperspectral remote sensing Multi-angular spectral measurement Powdery mildew Sensitive wave bands Winter wheat powdery mildew winter wheat hyperspectral remote sensing multiangular Angle Wheat look angles (electronics) Canopies Winter

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Multi-granular model to solve netted problem

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Journal of Computational Information Systems 2013年第19期9卷 7919-7927页

作者： Chen, Jie Zhang, Yanping Zhao, Shu Liu, Lulu School of Computer Science and Technology Anhui University Hefei 230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China Department of Computer Science and Technology Hefei Normal University Hefei 230061 China

The complex problems usually have netted structure, namely netted problems. The generally solving methods are based on sequence-searching or tree-searching of this kind of problems. But the structure of netted problems isn't merely sequence or tree. The Multi-granular Model was proposed in this paper which is put forward based on granular transaction of Quotient Space Theory. The whole problem is represented as a directed graph. Firstly, this graph was projected by constraints of original problem into coarse-grained spaces. Then granular decomposition is used to clear up the circle paths in new graph. In optimal quotient space, we search the answers according to the ordered sequence which is got by traversing the result of granular decomposition. In this paper, an applicable example is given and experiment contrasted with traditional tree searching method shows that this algorithm spends less time complexity and smaller space complexity. © 2013 Binary Information Press.

关键词： Directed graphs

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A quasi-static clustering algorithm in mobile heterogeneous sensor network

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Journal of Computational Information Systems 2013年第9期9卷 3741-3749页

作者： Wang, Bingting Lin, Qibin Hu, Yanjun Liang, Hui Wang, Xianbing Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Mechanical and Electronic Engineering Chuzhou University Chuzhou 239000 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China

In this paper, we constructed the architecture of mobile heterogeneous sensor network by introducing user equipments (UEs) in static wireless sensor network. We analyzed the failure of traditional static clustering algorithm, gave a set of parameters that affected the performance of cluster heads in the mobile environment and proposed a Quasi-Static Clustering Algorithm (QSCA). Through theoretical analysis and simulation, this algorithm can reduce average delay and prolong network lifetime. We verified the adaptability of QSCA algorithm to energy consumption and dynamic topology by comparing with the LEACH algorithm. © 2013 by Binary Information Press.

关键词： Clustering algorithms

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