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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

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

ISBN: (纸本)9781424469062

The high-order finite-difference time-domain (HO-FDTD) technique is used in the simulation of ground-penetrating radar modeling in three dimensions (3-D), which can improve accuracy and reduce the error caused by numerical dispersion effectively. To absorb waves reflected from edges we implement convolutional perfectly matched layer (CPML) absorbing boundaries. It can efficiently absorb the reflections and greatly increase the computation efficiency. The surface-based reflection and cross-hole GPR modeling are simulated, and numerical results show the efficiency of the method. ©2010 IEEE.

关键词： Ground penetrating radar systems

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An efficient splitting the plane-wave FDTD method

An efficient splitting the plane-wave FDTD method

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2010 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2010

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

ISBN: (纸本)9781424457052

The paper presents a new efficient method of introduction of plane wave source into finite difference time domain (FDTD) grids: the method of splitting the plane-wave FDTD (SP-FDTD). The new equations for the 1-D propagator are based on spitted-field Maxwell's equations, and the propagator makes the 1-D and 2-D dispersion equations identical. The technique virtually eliminates numerical dispersion, filed location and polarization mismatches between propagator and main grid, for a plane wave propagating at an angle forming an integer grid cell ratio, which can represent almost any angle in theory. Through the leak test of the different incident angles of the Gauss pulse plane wave source in 2-D, it shows that, the technique can achieve a perfect total-field scattered-field separation, making leakage down to -340 dB levels. © 2010 IEEE.

关键词： Maxwell equations

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The SP-FDTD method for High-Order FDTD Plane Wave Injection

The SP-FDTD method for High-Order FDTD Plane Wave Injection

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第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

作者： Lei Wu Zhi-xiang Huang Hui Wang Jia-xun Sun Xin-gang Ren Xian-liang Wu Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

In the paper, the method of splitting plane wave FDTD (SP-FDTD) algorithm, an efficient method of introducing plane wave source into finite difference time domain grids, is presented for solving oblique incident wave for the modified high-order FDTD (M24 scheme). Numerical examples in 2-D demonstrate the valid of the method and normalized field leakage was measured at -320 dB levels.

关键词： Time domain analysis Finite difference methods Antennas

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An Efficient Splitting the Plane-wave FDTD Method

An Efficient Splitting the Plane-wave FDTD Method

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2010 International Conference on Microwave and Millimeter Wave Technology(2010国际微波与毫米波技术会议 ICMMT2010)

作者： Wang Hui Huang Zhi-xiang Liu Xiao-yong Wu Xian-liang Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

关键词： Finite difference time domain total-field scattered-field separation the method of splitting the plane-wave FDTD (SP-FDTD)

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Design of image-reject hairpin filter applied for Ku-band LNB

Design of image-reject hairpin filter applied for Ku-band LN...

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第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

作者： Zhi-xiang Huang Hui Wang Yan Zhou Jia-xun Sun Xian-liang Wu Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

An image-reject hairpin bandpass filter used in Ku-band low noise block (LNB) is designed, and optimized in the paper. The designed detail of the filter is explained and the image-reject is illustrated theoretically. According to the research, under the condition of reducing the size as small as possible, the hairpin filter used in Ku-band LNB we designed not only can satisfy the demands from bandwidth and return loss, but also has good image-reject. In the end, the results of the simulation and measurement are presented, which prove the feasibility of our design.

关键词： Lead Optimization Artificial neural networks Frequency conversion Measurement uncertainty Bandwidth

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Manifold Feature Extraction for Video Based on Locally Linear Embedding

Manifold Feature Extraction for Video Based on Locally Linea...

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The 5th International Conference on Computer Science & education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Maosheng Fu Qin Xu Bin Luo Min Kong Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui UniversityHefei Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui UniversityHefei

Locally linear embedding (LLE) is an elegant nonlinear method for feature extraction and manifold learning, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. However, LLE algorithm fails when it is directly applied to video with multi-shot. In this paper, video manifold feature is defined firstly, and then using LLE we extract video manifold feature through adding virtual frames on an enriched set. The proposed manifold feature extraction method is applied to shot transition and video trajectories. The video manifold feature description gives a new tool for video analysis.

关键词： Feature extraction:Linear locally embedding Video

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD. ©2010 IEEE.

关键词： Discriminant analysis

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Manifold feature extraction for video based on locally linear embedding

Manifold feature extraction for video based on locally linea...

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International Conference on Computer Science and education

作者： Fu, Maosheng Xu, Qin Kong, Min Luo, Bin Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Computer Science and Technology West Anhui University Anhui Lu'an 237012 China

ISBN: (纸本)9781424460052

关键词： Feature extraction

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Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

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Journal of Electronic Science and Technology 2010年第2期8卷 183-186页

作者： De-Xiang Zhang Xiao-Pei Wu Zhao Lv Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition （EMD） algorithm and Teager energy operator （TEO） is proposed to locate endpoint intervals of a speech signal embedded in noise. 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 TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Index Terms----Empirical mode decomposition endpoint detection noisy speech Teager energy operator.

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SPEECH ENDPOINT DETECTION IN NOISY ENVIRONMENTS USING EMD AND TEAGER ENERGY OPERATOR

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Journal of Electronic Science and Technology 2010年第2期000卷 183-186页

作者： DE-XIANG ZHANG XIAO-PEI WU ZHAO Lü Key Lab.of Intelligent Computing and Signal Processing of Ministry of Education.Anhui University Hefei 230039China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. 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 TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Empirical mode decomposition endpoint detection noisy speech Teager energy operator

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