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Chinese Control Conference (CCC)

作者： Rong Hong Liang Yiming Wu Ronghui Xu Cheng Yu Fe College of Electrical and Information Engineering Hunan University Changsha China College of Computer & Communication Hunan University Changsha China Provincial Key Laboratory of Image Processing & Imagecom Communication Nanjing University of Posts and Telecommunications Nanjing China

Through a series of real tests, this paper analyses the characteristic of IEEE 802.11 traffic, explains the results of the tests. More importantly, the results indicate that the characteristic of IEEE 802.11 traffic exhibits obviously self-similarity. As the first step to set up a 802.11 traffic math-model based on self-similarity theory.

关键词： Wireless LAN Telecommunication traffic Traffic control Educational institutions Testing communication system traffic control image processing Telecommunication computing

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Direct Measure of Local Region Functional Connectivity by Multivariate Correlation Technique

Direct Measure of Local Region Functional Connectivity by Mu...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Hui Zhang Jie Tian Zonglei Zhen Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China

In order to identify the local areas whose activity are most similar with region of interest (ROI), we usually compute the correlation of fMRI data for the brain functional connectivity. The fMRI data is usually noisy, extraction of functional connectivity with the voxel by voxel based method such as Pearson correlation analysis is not robust. Many people smooth the fMRI data before compute the correlation coefficient, which only makes the effect worse, because some useful original information is lost during the smoothing. Here, we analyzed this issue in details and improved the data processing flow to make the result better. Furthermore, a new criterion RV correlation coefficient was introduced in this article to measure the correlation between two local brain regions; This multivariate correlation technique applied the spatiotemporal information within the local regions to measure the similarity of the activity in different brain regions. We compared four different strategies mentioned above to detect the functional connectivity on the simulated and real fMRI data, and the results demonstrated that the RV-coefficient method obtained the best performance.

关键词： Smoothing methods Data mining Spatiotemporal phenomena Distortion measurement Kernel Hemodynamics Correlation Multidimensional systems Statistics Robustness

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Motion compensation optimization of H.264 decoder based on DSP hardware platform

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Nanjing Youdian Daxue Xuebao (Ziran Kexue Ban)/Journal of Nanjing University of Posts and Telecommunications (Natural Science) 2007年第2期27卷 80-84页

作者： Gan, Zong-Liang Wang, Kai Zhu, Xiu-Chang Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

The H.264 video coding standard has a significant performance benefit versus former standards. However, motion compensation decoding process takes up a significant decoding time due to the advanced coding features. In this paper, the theory of motion compensation decoding in H.264 is given at first. Then the improved method is proposed by motion compensation fast decoding algorithm and optimization based on ADI Blackfin533 hardware platform. Both PC and ADI Blackfin533 experimental results show that the proposed optimization strategy can substantially improve the efficiency of real-time H.264 decoder.

关键词： Digital signal processor Direct memory access H.264 Motion compensation decoding

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Multi-sensor moving target tracking using particle filter

Multi-sensor moving target tracking using particle filter

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IEEE International Conference on Robotics and Biomimetics

作者： Guocheng Liu Yongji Wang Chinese Education Ministry Key Laboratory for Image Processing and Intelligence Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hebei China

ISBN: (纸本)9781424417612;1424417619

The principle of target tracking and data fusion techniques are discussed. To resolve high uncertainty that exists in sensors of mobile robots, the cross-sensor and cross-modality (CSCM) data fusion algorithm is presented. The algorithm is based on particle filter techniques, fuses the information coming from multiple sensors and merges different state space models. So it can be used to eliminate system and measurement noise and estimate value of position and heading of mobile robot. On simulation experiments, we compare different cases such as single sensor and multi-sensor data fusion, the results demonstrate the feasibility and effectiveness of this algorithm and exhibits good tracking performance.

关键词： Target tracking Particle filters Mobile robots Sensor fusion Hidden Markov models Sensor systems Intelligent robots Intelligent sensors Noise measurement State estimation

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Camera Calibration for 3D Color Scanning System Using Virtual 3D Model

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Computer Aided Drafting,Design and Manufacturing 2007年第2期17卷 77-81页

作者： SUN Xian-bin LI De-hua YIN Jie YAO Xun State Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Hubei University of Technology Wuhan 430068 China

Instead of traditionally using a 3D physical model with many control points on it, a calibration plate with printed chess grid and movable along its normal direction is implemented to provide large area 3D control points with variable Z values. Experiments show that the approach presented is effective for reconstructing 3D color objects in computer vision system.

关键词： computer vision 3D scan camera calibration calibration plate

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Principal Component Analysis of fMRI Data in Local Frequency Domain

Principal Component Analysis of fMRI Data in Local Frequency...

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2007 IEEE/ICME International Conference on Complex Medical Engineering-CME2007(CME2007 第二届国际复合医学工程学术大会)

作者： Zonglei Zhen Jie Tian Hui Zhang Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Science P.O.Box 2728 Beijing 100080 China

Most established activation detection techniques for functional magnetic resonance imaging(fMRI) data are always based on oversimplified assumptions that no spatial or temporal correlations exist in the data. In this article, we strive for analysis of fMRI data in local frequency domain with multitaper frequency-domain singular value decomposition(MTM-SVD) technique which explicitly takes into account the intrinsic spatiotemporal correlations in the data and allows modeling patterns of spatiotemporal dynamics of brain activity. A local frequency-based representation well captures the features of BOLD signal evoked by experimental designs with periodic stimuli and the dominant physiology noise, therefore we can utilize principal component analysis to decompose fMRI data in local frequency domain and extract the spatiotemporal patterns of the brain activity. We have made experiment on real fMRI data, and the results demonstrated that our approach could detect the brain activity patterns effectively and reliably.

关键词： Principal component analysis Frequency domain analysis Spatiotemporal phenomena Magnetic resonance Data analysis Pattern analysis Magnetic analysis Brain modeling Design for experiments Physiology

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An Insight into the Estimation of MIMO Propagation Parameters using the Sage Algorithm

An Insight into the Estimation of MIMO Propagation Parameter...

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The Second European Conference on Antennas and Propagation, EuCAP 2007

作者： M. Matthaiou N. Razavi-Ghods D.I. Laurenson S. Salous Institute for Digital Communications Joint Research Institute for Signal and Image Processing University of Edinburgh UK Cavendish Laboratory University of Cambridge Cambridge U.K. Centre for Communication Systems University of Durham Durham UK

In this contribution, we provide a thorough review of the application of SAGE (space-alternating generalised expectation-maximisation) algorithm to the problem of parameter estimation for MIMO (multiple-input multiple-output) systems. It is well established that the SAGE algorithms yields a superior performance compared to other estimation algorithms in terms of accuracy and robustness. For our investigation, we consider both the time and frequency domain evaluations of the algorithm since each domain requires a different signal model.

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A genetic algorithm for solving multi-constrained function optimization problems based on KS function

A genetic algorithm for solving multi-constrained function o...

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Congress on Evolutionary Computation

作者： Jianhua Xiao Jin Xu Zehui Shao Congfeng Jiang Linqiang Pan Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China School of Hydropower and Information Engineering Huazhong University of Science and Technology Wuhan China

In this paper, a new genetic algorithm for solving multi-constrained optimization problems based on KS function is proposed. Firstly, utilizing the agglomeration features of KS function, all constraints of optimization problems are agglomerated to only one constraint. Then, we use genetic algorithm to solve the optimization problem after the compression of constraints. Finally, the simulation results on benchmark functions show the efficiency of our algorithm.

关键词： Genetic algorithms Constraint optimization Mathematical model Testing Operations research Mathematics Industrial engineering Optimization methods Quadratic programming Robustness

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GPU parallel computing architecture and CUDA programming model

GPU parallel computing architecture and CUDA programming mod...

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IEEE Hot Chips Symposium (HCS)

作者： John Nickolls Electronics and Computer Science Faculty of Computer University of Zielona Góra Góra Poland Shaanxi Provincial Key Laboratory of Speech and Image Information Processing the School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9781467388702

This article consists of a collection of slides from the author's conference presentation on NVIDIA's CUDA programming model (parallel computing platform and application programming interface) via graphical processing units (GPU). Some of the specific topics discussed include: the special features of GPUs; the importance of GPU computing; system specifications and architectures; processing capabilities; parallel memory sharing; CUDA programming models; transparent scalability; and major applications supported.

关键词： Instruction sets Graphics processing units Parallel processing Computer architecture Programming Computational modeling

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Designing of laser marking software based on VC++6.0

Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/...

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Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) 2007年第1期31卷 154-156页

作者： Deng, Zhixiang Wang, Yongji Department of Control Science and Technology Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

Designing of universal software in laser-marking industry is introduced here. This software boasts versatile functions, from basic graphic drawing to input interface for files created in AutoCAD and CorelDRAW, Graphics and images showed in the user interface, which can be transformed by such methods as aligning, filling, node adjusting, are interpolated to discrete point data and then downloaded to control laser marking machine via PCI board card to accomplish total marking process. Object oriented programming methods are used, which make this software expansive and maintainable with a friendly interface easy to operate for clients.

关键词： Glyph filling Glyph import Laser marking VC++

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