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The Second Asian Conference on Membrane computing(ACMC2013)

作者： Xingyi Zhang Dong Qin Zhuanlian Ding Jin Tang Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University

Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as the structure of P systems, the way of communication between cells, etc. Membrane algorithms are a kind of parallel methods, where many operations can be performed in parallel. Although the importance of the parallelism of such algorithms is recognized, membrane algorithms were often implemented on the serial computing device Central processing Unit (CPU), which makes the algorithms cannot work in a more efficient way. In this work, we consider the implementation of membrane algorithms on the parallel computing device Graphics processing Unit (GPU). Under such implementation, all cells of membrane algorithms can work simultaneously. Experiment results on two classical intractable problems, point set matching problem and TSP, show that GPU implementation of membrane algorithms is much more efficient than CPU implementation in terms of runtime, especially for solving the problems with a high complexity.

关键词： Membrane computing Membrane algorithm Parallel computing device GPU

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Low-cost circuit design of EEG signal acquisition for the brain-computer interface system

Low-cost circuit design of EEG signal acquisition for the br...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Lei Zhang Xiao-jing Guo Xiao-pei Wu Beng-yan Zhou Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

Increasing number of research activities and different types of studies in brain-computer interface systems (BCIs) show potential in this young research area. However, BCIs have not become widely applied, most of them are still limited in the lab.ratory and off-line. One of the important reasons is that: EEG signal acquisition is completed by the professional medical equipments. They are expensive and the parameters of them cannot be flexiblely changed with the specific BCI experiment paradigm. In the paper, a single-channel low-cost circuit of EEG signal acquisition for the BCI system is designed. The circuit is composed of protection circuit, instrumentation amplifier, common mode rejection (CMR) circuit, gain adjustable amplifiers and filters. In order to test this circuit, the circuit simulation and the real-time EEG measurements are implemented. The experimental results show that the circuit is effective with good performance, it is very suitable for the online BCI system.

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Accelerated Plasma Simulations using the FDTD Method and the CUDA Architecture

Accelerated Plasma Simulations using the FDTD Method and the...

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2013 International Symposium on Antennas and Propagation(2013天线与传播国际会议)

作者： Wei Meng Yufa Sun Key Lab or Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei P.R.China

This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-transform-based finite-difference time-domain (ZTFDTD) method was presented for simulating the interaction of electromagnetic wave with unmagnetized *** using the newly introduced Compute Unified Device Architecture (CUDA) technology, we illustrate the efficacy of GPU in accelerating the FDTD computations by achieving significant speedups with great ease and at no extra hardware *** effect of the GPU-CPU memory transfers on the speedup will be also studied.

关键词： GPU FDTD Z-transform CUDA

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A model of three points for location estimation in wireless sensor networks

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

作者： Xie, Shao Guo Hu, Yan Jun Wang, Yi Jiang, Fang Liu, Jing Jing Wang, Ying Guan Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education AnHui University Hefei China Key Laboratory of Wireless Sensor Network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai 200050 China

ISBN: (纸本)9783037858028

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. © (2013) Trans Tech Publications, Switzerland.

关键词： Location

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Linear projective non-negative matrix factorization

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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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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 availab.e. 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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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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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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Calculation of Casimir force using FDTD method

Calculation of Casimir force using FDTD method

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2012 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2012

作者： Wang, Wang Huang, Zhixiang Wu, Bo Shen, Jing Ding, Ming Wu, Xianliang Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei China

ISBN: (纸本)9781467321839

Casimir effect is the vacuum attractive force between two neutral conducting plates. Physicists have developed some methods to calculate the Casimir effect. We will use Maxwell's stress tensor to calculate the force with statistical thermodynamics, mode functions and Green functions. With the FDTD method, we can accurately calculate the Casimir force arises from the configuration of arbitrary geometry and any medium. To illustrate this method we will demonstrate the calculation of the Casimir force in a simple 2-dimension piston-like configuration and observe changes in the force due to changes of the configuration. © 2012 IEEE.

关键词： Stress tensor

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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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