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Linear projective non-negative matrix factorization

ICIC Express Letters 2013年第8期7卷 2285-2291页

作者： Hu, Lirui Wu, Jianguo Wang, Lei Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University No. 3 Feixi Road Hefei 230039 China School of Computer Science and Technology Nantong University No. 9 Seyuan Road Nantong 226019 China School of Computer Science and Technology Anhui University No. 3 Feixi Road Hefei 230039 China

In order to solve the problem that the iterative method for Linear Projection- Based Non-negative Matrix Factorization (LPBNMF) is complex, a method, called Linear Projective Non-negative Matrix Factorization (LP-NMF), is proposed. In LP-NMF, from projection and linear transformation angle, an objective function of Frobenius norm is defined. The Taylor series expansion is used. An iterative algorithm for basis matrix and linear transformation matrix is derived, and a proof of algorithm convergence is provided. Experimental results show that the algorithm is convergent;relative to Nonnegative Matrix Factorization (NMF), the orthogonality and the sparseness of the basis matrix are better;in face recognition, there is higher recognition accuracy. The method for LP-NMF is effective. © 2013 ICIC International.

关键词： Linear transformations

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Study on the Gain Material with Four Energy Level Model Using FDTD Method

Study on the Gain Material with Four Energy Level Model Usin...

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The International Symposium on Photonics and Optoelectronics(SOPO 2013)

作者： Hui Xue Zhixiang Huang Xianliang Wu Key Laboratory of Intelligent Computing and Signal Processing Anhui University Department of Physics and Electronic Engineering Hefei Normal University

A faster numerical method based on FDTD for the four energy level atomic system is present here. The initial conditions for the electrons of each level are achieving while the fields are in steady state. Polarization equation, rate equations of electronic population and Maxwell's equations were used to describe the coupling between the atoms and electromagnetic wave. Numerical simulations, based on a finite-difference time-domain (FDTD) method, were utilized to obtain the population inversion and lasing threshold. The validity of the model and its theory is confirmed. The time, which we can observe the lasing phenomenon, is much shorter in our new model. Our model can be put into using in large scale simulations in mutiphysics to reduce the total simulated time.

关键词： Finite-Difference Time-Domain Gain Material Lasing

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A fuzzy supervised learning method with dynamical parameter estimation for nonlinear discriminant analysis

A fuzzy supervised learning method with dynamical parameter ...

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作者： Song, Xiaoning Liu, Zi Yang, Xibei Yang, Jingyu School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang 212003 China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing 210094 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

In this paper, we develop a novel fuzzy supervised learning algorithm based on the dynamical parameter estimation. First, a reformative supervised fuzzy LDA algorithm (RF-LDA) for the training samples is proposed. Compared with the conventional fuzzy LDA algorithm, the presented algorithm computes the discriminant vectors associated with the membership grade from each training sample, which is theoretically effective in overcoming the classification limitation originating from the imprecise samples. Second, when a novel fuzzy LDA model is required in order to take some decision about the feature extraction and classification, the dynamical parameter estimation method of the fuzzy LDA model should recursively process the measured data as they become available. In the line of previous arguments, we approach the problem of control parameter estimation of RF-LDA by considering the formulation of a Hopfield Neural Network (HNN), which is named HRF-LDA. Third, considering the fact that the Kernel Fisher Discriminant (KFD) is effective in extracting the nonlinear discriminative information of the feature space by using kernel trick, a kernel version of HRF-LDA is presented subsequently, which has the potential to outperform the traditional fuzzy learning algorithms, especially in the cases of nonlinear small sample sizes. The advantage of this learning algorithm is that it successfully utilizes the improved kernel fuzzy LDA algorithm as a supervised feature extraction tool. Meanwhile, by means of the control parameter estimation, we address the problem that the particular value of offset in the calculation of the grade of membership is dynamically assigned. Extensive experimental studies conducted on the ORL, NUST603, FERET, Yale and XM2VTS face images show the effectiveness of the proposed fuzzy integrated algorithm. © 2013 Elsevier Ltd. All rights reserved.

关键词： Parameter estimation

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Nitrogen vertical distribution by canopy reflectance spectrum in winter wheat

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IOP Conference Series: Earth and Environmental Science 2014年第1期17卷

作者： W J Huang Q Y Yang D L Peng L S Huang D Y Zhang G J Yang Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100094 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 Anhui China Beijing Agriculture Information Technology Research Center Beijing 100097 China

Nitrogen is a key factor for plant photosynthesis, ecosystem productivity and leaf respiration. Under the condition of nitrogen deficiency, the crop shows the nitrogen deficiency symptoms in the bottom leaves, while excessive nitrogen will affect the upper layer leaves first. Thus, timely measurement of vertical distribution of foliage nitrogen content is critical for growth diagnosis, crop management and reducing environmental impact. This study presents a method using bi-directional reflectance difference function (BRDF) data to invert foliage nitrogen vertical distribution. We developed upper-layer nitrogen inversion index (ULNI), middle-layer nitrogen inversion index (MLNI) and bottom-layer nitrogen inversion index (BLNI) to reflect foliage nitrogen inversion at upper layer, middle layer and bottom layer, respectively. Both ULNI and MLNI were made by the value of the ratio of Modified Chlorophyll Absorption Ration Index to the second Modified Triangular Vegetation Index (MCARI/MTVI2) referred to as canopy nitrogen inversion index (CNII) in this study at ±40° and ±50°, and at ±30° and ±40° view angles, respectively. The BLNI was composed by the value of nitrogen reflectance index (NRI) at ±20° and ±30° view angles. These results suggest that it is feasible to measure foliage nitrogen vertical-layer distribution in a large scale by remote sensing.

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A Model of Three Points for Location Estimation in Wireless Sensor Networks

A Model of Three Points for Location Estimation in Wireless ...

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2013 2nd International Symposium on Materials Science and Engineering Technology(ISMSET 2013)

作者： Shaoguo Xie Yanjun Hu Yi Wang Fang Jiang Jingjing Liu Yingguan Wang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education An Hui University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences

In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks(WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength(RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP(ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the localization accuracy for WSNs. Moreover, the localization accuracy of the proposed models in scenario 2 with random deployment of anchor nodes are better than in scenario 1 with planned deployment of anchor nodes. Additionally, compared with MMSE and BML, ETP and TP can reduce the environmental impact on location estimation.

关键词： Location estimation Anchor node Wireless sensor networks

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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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未来视频技术专题(英文)

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China Communications 2013年第5期 8-10页

作者：陈熙霖朱秀昌王桥胡栋 Ming-Ting SUN the Institute of Computing Technology Chinese Academy of Sciences (CAS) the IEEE Transactions on Image Processing the Journal of Computer Science and Technology the Chinese Journal of Computers College of Communications and Information Engineering NUPT Image Processing and Image Communications Key Laboratory of Information Industrial Ministry and Jiangsu Province Signal and Information Processing Laboratory Southeast University

In the past few years, video has become one of the most powerful engines to push communications forward. The increasing of digital video technology requires larger and larger bandwidth for various applications, such as IPTV, VOD, video phone, mobile search, etc. The goal of this Feature Topic column is to present and highlight the latest progress and future video-related technologies. We hope this

关键词： IEEE over

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Fusion of multi-spectral image and panchromatic image based on support vector regression

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Journal of Beijing Institute of Technology 2012年第2期21卷 269-277页

作者：胡根生梁栋 Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi- spectral image and the panchromatic image are fused based on regions at different levels. Our experi- ments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image.

关键词： image processing image fusion support vector regression super-resolution

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Corrigendum to “A user-specific and selective multimodal biometric fusion strategy by ranking subjects” [Pattern Recognition 46 (2013) 3341–3357]

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Pattern Recognition 2014年第1期47卷 493-493页

作者： Norman Poh Arun Ross Weifeng Li Josef Kittler Department of Computing University of Surrey Guildford GU27XH UK West Virginia University Morgantown WV 26506 USA Shenzhen Key Laboratory of Information Science & Technology Shenzhen Engineering Laboratory of IS&DRM Department of Electronic Engineering/Graduate School at Shenzhen Tsinghua University China Centre for Vision Speech and Signal Processing (CVSSP) FEPS University of Surrey Guildford GU27XH UK

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A novel high order time-domain scheme for 2D quantum problem

A novel high order time-domain scheme for 2D quantum problem

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2012 5th Global Symposium on Millimeter-Waves, GSMM 2012

作者： Sun, Bingbing Wang, Hui Wu, Xianliang Huang, Zhixiang Liu, Zheng Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9781467313032

An explict fourth order finite difference time do-main(FDTD) scheme is applied to quantum simulation. The analysis of stablity and dispersion relation of this technique is presented in this article. A strict time bound is derived to ensure stability. The numerical scheme used here is different from the scheme in electromagnetic field. Several numerical experiments are illustrated to verify the efficiency of the new method. Some useful physics results such as eigenfrequency and eigenenergy are also obtained. © 2012 IEEE.

关键词： Electromagnetic fields

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