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SICE Annual Conference

作者： Ho-Nien Shou Chen-Tsung Lin Chung-Liang Chang Department of Aviation & Communication Electronics Air Force Institute of Technology USA Flight Control Division National Space Organization Hsinchu Taiwan Department of Biomechatronics Engineering National Pingtung University of Science and Technology Ping Tung Taiwan

This paper presents the micro-satellite three axis attitude angle rate estimated from nonlinear filtering design method known as Unscened Kaiman Filter(UKF). It uses magnetometer (Earth s magnetic field) as the sole measurement sensor for satellite attitude angle rate determination without rate gyro and priori knowledge of the spacecraft state. Simulation results show that the algorithm can quickly converge even for large initial attitude state, and is accuracy and efficient.

关键词： Quaternions Mathematical model Kalman filters Position measurement Equations Satellites Magnetic fields

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OpenCV 2.0 (3): Introduction of various image processing functions and face detection

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Kyokai Joho Imeji Zasshi/Journal of the institute of Image Information and Television Engineers 2010年第9期64卷 1362-1366页

作者： Suenaga, Tsuyoshi Ido, Junichi Koeda, Masanao Etsuko, Ueda Nara Institute of Science and Technology Graduate School of Information Science Nara Japan Osaka Electro-Communication University Department of Computer Sceicncc Osaka Japan Nara National College of Technology Department of Control Engineering Nara Japan Kawada Industries Inc. Tochigi Japan

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Diesel engine fault diagnosis method based on MPDE-SVM and its application

Diesel engine fault diagnosis method based on MPDE-SVM and i...

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International Conference on Information Science and engineering (ICISE)

作者： Cao, Longhan Wu, Mingliang He, Junqiang Liu, Lu Liu, Xiaoli Key Laboratory of Control Engineering Chongqing Communication Institute Chongqing 400035 China Key Laboratory of Manufacture and Test Techniques for Automobile Parts Ministry of Education Chongqing University of Technology Chongqing 400050 China

ISBN: (纸本)9781424480968

There is much difficulty in fault diagnosis because of lacking of system fault samples. So this paper presents a mixed strategy of combining differential evolution algorithm with local enhanced operator with the optimization of the parameters of support vector machine. For the diesel engine valve clearance fault diagnosis, the measured diesel engine valve vibration signals data after wavelet transform are used as the characteristic values of the diagnostic model. Then the diesel engine valve clearance fault diagnosis model of SVM based on MPDE is established and compared with the BPNN, SVM and IQPSO-RBF models, The results showed that the performance of the SVM optimized by MPDE algorithm is better than the models based on the other three algorithms. The method is practical and effective. © 2010 IEEE.

关键词： Failure analysis

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Image restoration method based on least-squares and regularization and fourth-order partial differential equations

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Information technology Journal 2010年第5期9卷 962-967页

作者： Yu, Xiaoyang Gao, Yuan Yang, Xue Shi, Chu Yang, Xiukun Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentation College of Measurement Control Technology and Communication Engineering Harbin University of Science and Technology No. 4 Lin Yuan Road Xiang Fang District Harbin City Heilongjiang Province 150040 China Shandong Academy of Sciences Institute of Oceanographic Instrumentation Corporate Research Center Jersey City NJ 07302 United States MOTOROLA Countries of Southern California to Identify R and D Center IDENTIX. Inc. Corporate Research Center Jersey City NJ 07302 United States

An image restoration method based on least-squares and regularization and fourth-order partial differential equations is proposed in this study. Noise is removed by improved Yu-Li and M. Kaveh's fourth-order partial differential equations method and then improved least-squares and regularization method is adopted to restored image. The experimental results show that the method can better restore degraded image and the peak signal to noise ratio and subjective visual effects of the restored image are improved significantly. © 2010 Asian Network for Scientific Information.

关键词： Image reconstruction

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New enhancement of infrared image based on human visual system

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Chinese Optics Letters 2009年第3期7卷 206-209页

作者：于天河李秋明戴景民 Department of Automation Measurement and Control Engineering Harbin Institute of Technology Computer Center Harbin University of Science and Technology School of Astronautics Harbin Institute of Technology

Infrared images are firstly analyzed using the multifractal theory so that the singularity of each pixel can be extracted from the images. The multifractal spectrum is then estimated, which can reflect overall characteristic of an infrared image. Thus the edge and texture of an infrared image can be accurately extracted based on the singularity of each pixel and the multifractal spectrum. Finally the edge pixels are classified and enhanced in accordance with the sensitivity of human visual system to the edge profile of an infrared image. The experimental results obtained by this approach are compared with those obtained by other methods. It is found that the proposed approach can be used to highlight the edge area of an infrared image to make an infrared image more suitable for observation by human eyes.

关键词： Imaging systems Infrared imaging Infrared spectroscopy Pixels

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An EEG-based classification system of Passenger's motion sickness level by using feature extraction/selection technologies

An EEG-based classification system of Passenger's motion sic...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yi-Hsin Yu Pei-Chen Lai Li-Wei Ko Chun-Hsiang Chuang Bor-Chen Kuo Chin-Teng Lin Institute of Electrical Control Engineering and Brain Research Center National Chiao Tung University Hsinchu Taiwan Graduate Institute of Educational Measurement and Statistics National Taichung University Taichung Taiwan Department of Biological Science and Technology and Brain Research Center National Chiao Tung University Hsinchu Taiwan

Past studies reported that the main electrogastrography (EEG) dynamic changes related to motion sickness (MS) were occurred in occipital, parietal, and somatosensory brain area, especially in the power increasing of the alpha band (8-13 Hz) and theta band (4-7 Hz) which had positive correlation with the subjective MS level. Depend on these main findings correlated with MS, we attempt to develop an EEG based classification system to automatically classify subject's MS level and find the suitable EEG features via common feature extraction, selection and classifiers technologies in this study. If we can find the regulations and then develop an algorithm to predict MS occurring, it would be a great benefit to construct a safe and comfortable environment for all drivers and passengers when they are cruising in the car, bus, ship or airplane. EEG is one of the best methods for monitoring the brain dynamics induced by motion-sickness because of its high temporal resolution and portability. After collecting the EEG signals and subjective MS level in a realistic driving environment, we first do the data pre-processing part including ICA, component clustering analysis and time-frequency analysis. Then we adopt three common feature extractions and two feature selections (FE/FS) technologies to extract or select the correlated features such as principal component analysis (PCA), linear discriminate analysis (LDA), nonparametric weighted feature extraction (NWFE), forward feature selections (FFS) and backward feature selections (BFS) and feed the feature maps into three classifiers (Gaussian Maximum Likelihood Classifier (ML), k-Nearest-Neighbor Classifier (kNN) and Support Vector Machine (SVM)). Experimental results show that classification performance of all our proposed technologies can be reached almost over 95%. It means it is possible to apply the effective technology combination to predict the subject's MS level in the real life applications. The better combination in thi

关键词： Feature extraction Electroencephalography Support vector machines Principal component analysis Classification algorithms Iron Accuracy

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Driver's cognitive state classification toward brain computer interface via using a generalized and supervised technology

Driver's cognitive state classification toward brain compute...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chun-Hsiang Chuang Pei-Chen Lai Li-Wei Ko Bor-Chen Kuo Chin-Teng Lin Institute of Electrical Control Engineering and Brain Research Center National Chiao Tung University Hsinchu Taiwan Graduate Institute of Educational Measurement and Statistics National Taichung University Taichung Taiwan Department of Biological Science and Technology and Brain Research Center National Chiao Tung University Hsinchu Taiwan

Growing numbers of traffic accidents had become a serious social safety problem in recent years. The main factor of the high fatalities was the obvious decline of the driver's cognitive state in their perception, recognition and vehicle control abilities while being sleepy. The key to avoid the terrible consequents is to build a detecting system for ongoing assessment of driver's cognitive state. A quickly growing research, brain-computer interface (BCI), offers a solution offering great assistance to those who require alternative communicatory and control mechanisms. In this study, we propose an alertness/drowsiness classification system based on investigating electroencephalographic (EEG) brain dynamics in lane-keeping driving experiments in a virtual reality (VR) driving environment with a motion platform. The core of the classification system is composed of dimension reduction technique and classifier learning algorithm. In order to find the suitable method for better describing the data structure, we explore the performances using different feature extraction and feature selection methods with different classifiers. Experiment results show that the accuracy is over 80% in most combinations and even near 90% under Principal Component Analysis (PCA) and Nonparametric Weighted Feature Extraction (NWFE) going with Gaussian Maximum Likelihood classifier (ML) and k-Nearest-Neighbor classifier (kNN), respectively. In addition, this developed classification system can also solve the individual brain dynamic differences caused from different subjects and overcome the subject dependent limitation. The optimized solution with better accuracy performance out of all combinations can be considered to implement in the kernel brain-computer interface.

关键词： Feature extraction Driver circuits Electroencephalography Classification algorithms Brain modeling Principal component analysis Support vector machines

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Implementation of a Novel Phoneme Recognition System using TMS320C6713 DSP

Implementation of a Novel Phoneme Recognition System using T...

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International Conference on VLSI Design

作者： J. Manikandan B. Venkataramani M. Bhaskar K. Ashish R. Raghul V. Mathangi Department of Electronics and Communication Engineering (ECE) National Institute of Technology Tricky (NITT) Department of Instrumentation and Control Engineering (ICE) National Institute of Technology Tricky (NITT)

ISBN: (纸本)9781424455416

A number of techniques have been proposed in the literature for phoneme based speech recognition system. In this paper, a technique for automatic phoneme recognition using zero-crossings (ZC) and magnitude sum function (MSF) is proposed. The number of zero-crossings and Magnitude sum function per frame are extracted and a Minimum Distance Classifier is proposed to recognize the phonemes in each frame with these features. In order to increase the recognition accuracy of phonemes, a finite state machine is also proposed. The performance of the proposed phoneme recognition system is evaluated using TTS database and compared with the system using Linear Predictive Coefficients (LPC) feature inputs. Phoneme recognition accuracies of 70.93% and 55.25% are obtained for the system using LPC and the one using ZC along with MSF respectively. However, using the finite state machine proposed in this paper, 100% recognition accuracy is obtained for both the techniques. The computational costs required for recognizing various sentences using both of the feature extraction techniques are evaluated. It is observed that the proposed technique requires about 9.3 times lower computational cost than the one using LPC. The proposed technique is adopted for the implementation of the phoneme recognition system on Texas Instruments TMS320C6713 floating point processor. The different ways to reduce the recognition time for the target device is explored and reported in this paper. The technique proposed here is also applicable for speech inputs from other database.

关键词： Phoneme Recognition Zero-crossings Magnitude Sum function LPC DSP

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Multiactuator panels for wave field synthesis: Evolution and present developments

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AES: Journal of the Audio engineering Society 2010年第12期58卷 1045-1063页

作者： Pueo, Basilio López, José J. Escolano, José Hörchens, Lars Communication and Social Psychology Department University of Alicante Alicante Spain iTeAM Institute Universidad Politecnica de Valencia Valencia Spain Telecommunication Engineering Department Polytechnic School University of Jaen Jaen Spain Laboratory of Acoustic Imaging and Sound Control Delft University of Technology Delft Netherlands

A technical review is presented of the development of a special type of planar loudspeaker array for wave field synthesis, known as multiactuator panel. It consists of a thin, stiff panel with a small back volume, which vibrates by means of a group of mechanical exciters, each driven by a different signal. Multiactuator panels are used as alternatives to arrays of classic loudspeakers with conically shaped diaphragms for wave field synthesis, with added benefits such as low visual profile and diffuse radiation. However, the use of multiactuator panel arrays poses some problems and technical challenges that have been described in the literature. A historical review of the evolution from single-to multi-excited panels is given, followed by a technical discussion of the current developments in the field of wave field synthesis reproduction by means of multiactuator panels.

关键词： Loudspeakers

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Monitoring mechanism to users' posting behavior based on Hash chain in wireless Mesh network

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Beijing Gongye Daxue Xuebao/Journal of Beijing University of technology 2010年第SUPPL. 2期36卷 119-122页

作者： Pan, Shao-Ming Yang, Ya-Tao Cai, Qi-Zhong Han, Jun-Feng Department of Electronic Information and Control Engineering Guangxi University of Technology Liuzhou 545006 Guangxi China Department of Communication Engineering Beijing Electronic Science and Technology Institute Beijing 100070 China

In order to solve the issue of users' posting behavior via wireless Mesh network, a monitoring mechanism to manage users' continuous posting behavior based on Hash chain is designed. When users access to the Mesh network and write a post, mutual authentication between users and gateway in Mesh network will be implemented firstly, after getting authorization from gateway, users can write new posts on the web server via Mesh network, the gateway in Mesh network forwards users' real and valid information to the web server. When the dissension about posting behavior occurs, web server can execute the non-repudiation tracing to users' posting behavior with the help of users' registrar server. Users' authorization keys can be created continuously by using of Hash chain in our scheme, which can achieve the real-time authorization during users' accessing the network for a long time. Based on this method, users' posting behavior via wireless Mesh network can be monitored and traced, the proposed scheme possesses better referential and practical application value.

关键词： Web services

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