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Numerical dispersion analysis of symplectic and ADI schemes

Numerical dispersion analysis of symplectic and ADI schemes

引用

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

作者： Ren, Xin-Gang Huang, Zhi-Xiang Wu, Xian-Liang Lu, Si-Long Mei, Yi-Cai Du, Hong-Mei Wang, Hui Shen, Jing Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China

ISBN: (纸本)9781467321839

In this paper, Maxwell's equations are taken as a Hamiltonian system and then written as Hamiltonian canonical equations by using the functional variation method. The symplectic and ADI schemes, which can be extracted by applying two types of approximation to the time evolution operator, are explicit and implicit scheme in computational electromagnetic simulation, respectively. Since Finite-difference time-domain (FDTD) encounter low accuracy and high dispersion, the more accurate simulation methods can be derived by evaluating the curl operator in the spatial direction with kinds of high order approaches including high order staggered difference, compact finite difference and scaling function approximations. The numerical dispersion of the symplectic and ADI schemes combining with the three high order spatial difference approximations have been analyzed. It has been shown that symplectic scheme combining with compact finite difference and ADI scheme combining with scaling function performance better than other methods. Both schemes can be usefully employed for simulating and solving the large scale electromagnetic problems. © 2012 IEEE.

关键词： Maxwell equations

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Study of periodic dispersive structures at oblique incidence by split-field FDTD method

Study of periodic dispersive structures at oblique incidence...

引用

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

作者： Lu, Si-Long Wu, Bo Huang, Zhi-Xiang Wu, Xian-Liang Ren, Xin-Gang Mei, Yi-Cai Du, Hong-Mei Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China

ISBN: (纸本)9781467321839

In this paper, the periodic structures are simulated by the split-field finite difference time domain (FDTD) method. By using this method, a set of auxiliary elements are introduced to represent the discretization of the Floquet transformed Maxwell's equations with oblique incidence. We here extend the split-field method to the study of 2D dispersive structures of Drude model combining with the Z transformation method. Some numerical experiments are presented to validate the code, and the obtained results are in good with the analytic results. © 2012 IEEE.

关键词： Finite difference time domain method

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Speech endpoint detection based on emd and spectral entropy in noisy environments

Speech endpoint detection based on emd and spectral entropy ...

引用

4th International Conference on Mechanical and Electrical Technology, ICMET 2012

作者： Liu, Yanli Zhang, Dexiang Ji, Mingwei The Institute of Mechanical and Electrical Engineering of Anhui University of Architecture Hefei 230601 China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)9783037855102

Accurate endpoint detection is crucial for speech recognition accuracy. A novel approach that finds robust features for endpoint detection based on the empirical mode decomposition (EMD) algorithm and spectral entropy in a noisy environment is proposed. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then spectral entropy can be used to extract the desired feature for IMF components. In order to show the effectiveness of the proposed method, we present examples showing that the new measure is more effective than traditional measures. The experiments show that the proposed algorithm can suppress different noise types with different SNR, and the algorithm is robust in the real signal tests. © (2012) Trans Tech Publications, Switzerland.

关键词： Intrinsic mode functions

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Irregular community discovery for cloud service improvement

Irregular community discovery for cloud service improvement

引用

作者： Liu, Jin Zhou, Jing Wang, Junfeng Zhang, Feng Liu, Fei State Key Lab. of Software Engineering Wuhan University Wuhan 430072 China Lab. of Complex Systems and Intelligence Science Institute of Automation CAS Beijing 100190 China State Key Lab. for Novel Software Technology Nanjing University Nanjing China School of Computer Science Communication University of China Beijing 100024 China Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100190 China College of Computer Science Sichuan University Chengdu 610064 China Software School Sun Yat-sen University Guangzhou 510006 China

Utility services provided by cloud computing rely on virtual customer communities forming spontaneously and evolving continuously. Clarifying the explicit boundaries of these communities is thus essential to the quality of utility services in cloud computing. Communities with overlapping features or prominent peripheral vertexes are usually typical irregular communities. Traditional community identification algorithms are limited in discovering irregular topological structures from CR networks, whereas these irregular shapes typically play an important role in finding prominent customers which are ignored in social CRM otherwise. We present a novel method of discovering irregular communities. It firstly finds and merges primitive maximal cliques and the irregular features of overlapping and prominent sparse vertices are further considered. An empirical case and a methodology comparison confirm the feasibility and efficiency of our approach. © 2012 Springer Science+Business Media, LLC.

关键词： Cloud computing

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STeC: A location-triggered specification language for real-time systems

STeC: A location-triggered specification language for real-t...

引用

作者： Chen, Yixiang MoE Engineering Research Center for Software/Hardware Co-design Technology and Application Shanghai Key Lab. for Trustworthy Computing East China Normal University Shanghai 200062 China

ISBN: (纸本)9780769546698

Internet of Things (IoT) or Cyber-Physical Systems (CPS) is a new trend of real-time systems in the area of information technology. This paper introduces a spatiotemporal consistence language for real-time systems (Shortly, STeC). The consistence requires that a process do its tasks at the required location or time. Thus, this language provides a location-triggered specification for real-time systems. The interaction between real-time agents deals with agent2agent communications. STeC looks like an extension of precess algebra CSP. But, the execution-time of actions and status of agents are stressed. Two kinds of interrupts time and interaction break are considered. Following the Dijkstra's guard style, nondeterministic choice phase guarded by communications is introduced. After setting up the syntax, its operational semantics is introduced. As an example, the railroad crossing problem is specified in terms of this language STeC. © 2012 IEEE.

关键词： Specification languages

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Perfect plane wave injection for symplectic finite-difference time-domain scheme

Perfect plane wave injection for symplectic finite-differenc...

引用

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

作者： Wang, Hui Huang, Zhi-Xiang Wu, Xian-Liang Wu, Bo Shen, Jing Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Department of Physics and Electronic Engineering Hefei Normal University Hefei 230061 China

ISBN: (纸本)9781467321839

In this paper, the method of splitting plane wave finite-difference time-domain (SP-FDTD) algorithm is presented for the initiation of plane wave sources in symplectic finite-difference time-domain (SFDTD) scheme. By splitting the fields on one-dimensional (1D) grid and using the nature of numerical plane wave in FDTD, an efficient plane wave sources is simulated on 1D grid, and a perfect match is achieved for a plane wave propagating at any angle forming an integer grid cell ratio. Numerical examples show the valid of the proposed method. © 2012 IEEE.

关键词： Wave propagation

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Interactive event detection in crowd scenes 12

Interactive event detection in crowd scenes

引用

4th International Conference on Internet Multimedia computing and Service, ICIMCS 2012

作者： Qin, Lei Cheng, Zhongwei Huang, Qingming Pang, Junbiao Key Lab. of Intel. Inf. Proc. Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University of Chinese Academy of Sciences Beijing China Beijing Municipal Key Lab. of Multimedia and Intelligent Software Technology Beijing Univ. of Tech. China

ISBN: (纸本)9781450316002

As an important aspect in video content analysis, event detection is still an open problem. In particular, the study on detecting interactive events in crowd scenes is still limited. In this paper, we investigate detecting interactive events between persons, e.g. PeopleMeet, PeopleSplitUp and Embrace in complex scenes using a sequence learning based approach. By sequence learning, the spatial-temporal context information is introduced in the learning stage. Experiments have been performed over TRECVid Event Detection 2010 dataset, which contains totally 144 hours surveillance video of London Gatwick airport. According to the TRECVid-ED 2010 formal evaluation, our approach obtains promising results, with the top performance (NDCR) for PeopleMeet and PeopleSplit-Up, and second-best performance (NDCR) for Embrace. Copyright © 2012 ACM.

关键词： Security systems

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Stock market volatility prediction: A service-oriented multi-kernel learning approach

Stock market volatility prediction: A service-oriented multi...

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2012 IEEE 9th International Conference on Services computing, SCC 2012

作者： Wang, Feng Liu, Ling Dou, Chenxiao State Key Lab. of Software Engineering Wuhan University Wuhan China College of Computing Georgia Institute of Technology Atlanta GA United States School of Computer Science Wuhan University Wuhan China

ISBN: (纸本)9780769547534

Stock market is an important and active part of nowadays financial markets. Stock time series volatility analysis is regarded as one of the most challenging time series forecasting due to the hard-to-predict volatility observed in worldwide stock markets. In this paper we argue that the stock market state is dynamic and invisible but it will be influenced by some visible stock market information. Existing research on financial time series analysis and stock market volatility prediction can be classified into two categories: in depth study of one market factor on the stock market volatility prediction or prediction by combining historical price fluctuations with either trading volume or news. In this paper we present a service-oriented multi-kernel based learning framework (MKL) for stock volatility analysis. Our MKL service framework promotes a two-tier learning architecture. In the top tier, we develop a suite of data preparation and data transformation techniques to provide a source-specific modeling, which transforms and normalizes a source specific input dataset into the MKL ready data representation. Then we apply data alignment techniques to prepare the datasets from multiple information sources based on the classification model we choose for cross-source correlation analysis. In the next tier, we develop model integration methods to perform three analytic tasks: (i) building one sub-kernel per source, (ii) learning and tuning the weights for sub-kernels through weight adjustment methods and (iii) performing multi-kernel based cross-correlation analysis of market volatility. To validate the effectiveness of our service oriented MKL approach, we performed experiments on HKEx 2001 stock market datasets with three important market information sources: historical prices, trading volumes and stock related news articles. Our experiments show that 1) multi-kernel learning method has a higher degree of accuracy and a lower degree of false prediction, compared to exist

关键词： Forecasting

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Immune clonal algorithm based feature selection for epileptic EEG signal classification

Immune clonal algorithm based feature selection for epilepti...

引用

2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012

作者： Peng, Yong Lu, Bao-Liang Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Univ. 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9781467303828

Detecting epileptic EEG signal automatically and accurately is significant in evaluating patients with epilepsy. In this study, the immune clonal algorithm (ICA) is employed to perform automatic feature selection, reducing the number of features the classifier deals with and improving the classification accuracy. In the experiment, EEG signal was decomposed into five sub-band components by a discrete wavelet transform. Features were extracted as input to train three classifiers (NB, SVM, KNN and LDA) to judge whether the EEG signal was epileptic or not. Then, ICA was introduced to select a feature subset to train the classifiers. Experimental results show that the classification accuracy based on selected features is significantly higher than that on original features. We also analyzed the relative importance of each feature. © 2012 IEEE.

关键词： Discrete wavelet transforms

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An insightful program performance tuning chain for GPU computing

An insightful program performance tuning chain for GPU compu...

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12th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2012

作者： Jia, Haipeng Zhang, Yunquan Long, Guoping Yan, Shengen Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences China College of Information Science and Engineering Ocean University of China China State Key Laboratory of Computing Science Chinese Academy of Sciences China Graduate University of Chinese Academy of Sciences China

ISBN: (纸本)9783642330773

It is challenging to optimize GPU kernels because this progress requires deep technical knowledge of the underlying hardware. Modern GPU architectures are becoming more and more diversified, which further exacerbates the already difficult problem of performance optimization. This paper presents an insightful performance tuning chain for GPUs. The goal is to help non-expert programmers with limited knowledge of GPU architectures implement high performance GPU kernels directly. We achieve it by providing performance information to identify GPU program performance bottlenecks and decide which optimization methods should be adopted, so as to facilitate the best match between algorithm features and underlying hardware characteristics. To demonstrate the usage of tuning chain, we optimize three representative GPU kernels with different compute intensity: Matrix Transpose, Laplace Transform and Integral on both NVIDIA and AMD GPUs. Experimental results demonstrate that under the guidance of our tuning chain, performance of those kernels achieves 7.8~42.4 times speedup compared to their naïve implementations on both NVIDIA and AMD GPU platforms. © 2012 Springer-Verlag.

关键词： Chains

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