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International Joint Conference on Neural Networks (IJCNN)

作者： Xuyang Lou Ruliang Wang Baotong Cui College of Communication and Control Engineering Jiangnan University Wuxi China Department of Information Technology Guangxi Teachers Education University Nanning China

By employing Lyapunov functions and Razumikhin techniques, we analyze the uniform boundedness and uniform asymptotic stability for a large class of impulsive neural networks with time-varying delay. Some new criteria are obtained to ensure the uniform boundedness and uniform asymptotic stability of the impulsive neural networks. The results remove the usual assumption that the activation functions f j (ldr) are of bounded, monotonous or differential character. Moreover, the time-varying delay function is not required to be differential. Therefore, the results which are easy to check and apply in practice, extend and improve the earlier publications.

关键词： Neural networks Asymptotic stability Lyapunov method Artificial neural networks Stability analysis Delay effects Stability criteria Sufficient conditions Frequency Differential equations

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Nonlinear predictive control based on online support vector machine

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Journal of Computational Information Systems 2009年第4期5卷 1165-1170页

作者： Du, Zhiyong Wang, Xianfang Henan Mechanical and Electrical Engineering College Henan Xinxiang 453002 China Henan Institute of Science and Technology Xinxiang 453003 China School of Communication and Control Engineering Jiangnan University Wuxi 214122 China

It is difficult to build an accurate model using the traditional predictive control algorithm for a nonlinear system. Because of the nonlinearity, time variation, the control quality is not ideal. A nonlinear predictive control algorithm based on online support vector machines model was proposed. The nonlinear model of the nonlinear system was obtained by online support vector machine to train a sequence data of input and output, and we can improve the system model accuracy online. The simulation results illustrate that the nonlinear predictive control using online SVM is effective. © 2009 Binary Information Press August, 2009.

关键词： Nonlinear systems

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Implementation and Evaluation of a Ubiquitous Health Monitoring System

Implementation and Evaluation of a Ubiquitous Health Monitor...

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International Conference on Complex, Intelligent and Software Intensive Systems, CISIS

作者： Akira Yamazaki Akio Koyama Junpei Arai Leonard Barolli Department of Informatics Graduate School of Science and Engineering Yamagata University Japan Department of Information and Control Engineering Yamagata College of Industry and Technology Japan Department of Information and Communication Engineering Fukuoka Institute of Technology Japan

ISBN: (纸本)9781424435692

In recent years, because of the birthrate declining and the elderly peoplepsilas population growing, the lack of doctors and the increase of the medical cost is becoming a big problem. One of solution for this problem is to prevent the humans from diseases in order to reduce the medical cost (e.g. by using the hospital as few times as possible). In this research, we have developed a wearable vital sensor which can be used anywhere without disrupting the everyday life of the patient. Furthermore, we have implemented a ubiquitous health monitoring system, which can confirm and share the sensor information received from a cellular phone attached to the wearable vital sensor immediately through the browser. This system can also send emergency report based on sensor information to the family and the doctor. In addition, we verified the system effectiveness by evaluating the implemented system.

关键词： Biomedical monitoring Wearable sensors Sensor systems Costs Senior citizens Humans Diseases Hospitals Patient monitoring Cellular phones

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Segment Clustering Radar Signal Sorting

Segment Clustering Radar Signal Sorting

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The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

作者： Qiang Guo Wei Xu Changhong Wang Di Guan Space Control and Inertial Technology Research Center Harbin Institute of Technology Harbin 15000 College of Information and Communication Engineering Harbin Engineering University Harbin 150001 Space Control and Inertial Technology Research Center Harbin Institute of Technology Harbin 15000 Harbin Normal University Harbin 150080 China

Radar signal sorting is picking-up pulse serial of same radar emitter from dense complex pulse signal flow. The tolerance of radar signal sorting is analyzed in modern electronic warfare. The complex and dense pulses environment makes it become a vital factor to restrict the efficiency of sorting of the conventional multi-parameters signal sorting system. A segment clustering radar signal sorting method is presented based on support vector clustering (SVC) according to the idea of statistics learning theory. It prevents tolerance from affecting radar sorting. The accuracy of sorting and the sensitivity of algorithm on parameter variation is analyzed. The experimental results show that the sorting method presented is effective to overcome the tolerance of radar signal sorting.

关键词： Sorting Pulse measurements Spaceborne radar Space technology Signal processing Radar measurements Space vector pulse width modulation Signal analysis Radio frequency Data mining

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Data Filtering Based Recursive Least Squares Parameter Estimation for ARMAX Models

Data Filtering Based Recursive Least Squares Parameter Estim...

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WRI International Conference on communications and Mobile Computing, CMC

作者： Yuwu Liao Dongqing Wang Feng Ding Department of Physics and Electronics Information Technology Xiangtan University Xiangtan China College of Automation Engineering Qingdao University of China Qingdao China School of Communication and Control Engineering Jiangnan University Wuxi China

This paper uses an estimated noise transfer function to filter the input-output data and presents a filtering based recursive least squares algorithm for ARMAX models. Through the data filtering, we obtain two identification models, one including the parameters of the system model, and the other including the parameters of the noise model. Thus, the recursive least squares method can estimate the parameters of these two identification models, respectively, by replacing unmeasurable noise terms in the information vectors with their estimates. The proposed F-RLS algorithm has high computational efficiency because the dimensions of its covariance matrices become small and can generate more accurate parameter estimation compared with other existing algorithms.

关键词： Least squares approximation Parameter estimation Autoregressive processes Recursive estimation Filtering algorithms Least squares methods Mobile communication Educational institutions Predictive models Mobile computing

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3D measurement technology based on gray coding light by combining gray code with trapezoidal phase shift

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2009年第SUPPL.期30卷 300-304页

作者： Shan, Lina Yu, Xiaoyang Fu, Xiao Wu, Haibin Chen, Deyun College of Measurement Control Tech. and Communication Engineering Harbin University of Science and Technology Harbin 150080 China

An 3D measurement scheme by combining Gray code with Trapezoidal phase-shift is presented. The scheme computes the relative intensity ratios in a Trapezoidal phase-shift period using Trapezoidal phase-shift pattern. Combining the Trapezoidal phase-shift with Gray code corresponding to sampling point, and the absolute intensity ratio of sampling point is determined. Then, 3D measurement is realized using projection geometry matrix model. Encoding and decoding principles by combining Gray code with Trapezoidal phase-shift are presented;period dislocation between Gray code and Trapezoidal phase-shift in course of decoding is analyzed, which could be corrected by judging the consistency between Gray code value increasing and phase mutation of adjacent pixels. Finally, simulation and real system were experimented. The experimental results indicate that relative measurement error of simulation system is about 0.0325% and that of real system is less than 4.0329%.

关键词： Decoding

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Subspace Semi-supervised Fisher Discriminant Analysis

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自动化学报 2009年第12期35卷 1513-1519页

作者： YANG Wu-Yi LIANG Wei XIN Le ZHANG Shu-Wu Hi-tech Innovation Center Institute of Automation Chinese Academy of Sciences Beijing 100190 P.R. China Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Minister of Education Xiamen University Xiamen 361005 P. R. China College of Oceanography and Environmental Science Xiamen University Xiamen 361005 P. R. China School of Electronics Information and Control Engineering Beijing University of Technology Beijing 100124 P. R. China

Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is maximized. Labeled data, however, often consume much time and are expensive to obtain, as they require the efforts of human annotators. In order to cope with the problem of effectively combining unlabeled data with labeled data to find the embedding transformation, we propose a novel method, called subspace semi-supervised Fisher discriminant analysis (SSFDA), for semi-supervised dimensionality reduction. SSFDA aims to find an embedding transformation that respects the discriminant structure inferred from the labeled data and the intrinsic geometrical structure inferred from both the labeled and unlabeled data. We also show that SSFDA can be extended to nonlinear dimensionality reduction scenarios by applying the kernel trick. The experimental results on face recognition demonstrate the effectiveness of our proposed algorithm.

关键词：费希尔判别分析法鉴别分析离散度降维方法

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Distribution of combustible gas alarm based on embedded Ethernet technology

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Journal of Harbin Institute of technology(New Series) 2008年第2期15卷 220-223页

作者：丁喜波张俊杰王洋 Space Optics Research Center School of AstronauticsHarbin Institute of Technology College of Measure-control Technology & Communication Engineering Harbin University Science and Technology Heilongjiang Provincial Institute of Measurement and Verification

One kind of combustible gas alarms based on industrial Ethernet was designed to prevent the gas leakage in industrial production sites, The alarm adopted the high performance microprocessor LPC2214 as the main chip. The embedded operating system μC/OS-Ⅱand TCP/IP protocol stack uIP running on LPC2214 constitute a development platform of application of the combustible gas alarm, The test shows that it can automatically and continuously detect combustible gas in industrial production sites in several positions;it can give out sound-light alarm and take protective measures immediately against the gas leakage; and it can send the detected data to PC through the Ethernet interface to realize the remote detection. The designed project provides a reference to design industrial devices based on industrial Ethernet

关键词： industrial Ethernet combustible gas alarm embedded system

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Subspace Semi-supervised Fisher Discriminant Analysis

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Acta Automatica Sinica 2009年第12期35卷 1513-1519页

作者： Wu-Yi YANG Wei LIANG Le XIN Shu-Wu ZHANG Hi-tech Innovation Center Institute of Automation Chinese Academy of Sciences Beijing 100190 P. R. China Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Minister of Education Xiamen University Xiamen 361005 P. R. China College of Oceanography and Environmental Science Xiamen University Xiamen 361005 P. R. China School of Electronics Information and Control Engineering Beijing University of Technology Beijing 100124 P. R. China

关键词： Fisher discriminant analysis (FDA) semi-supervised learning manifold regularization dimensionality reduction

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Gene expression data classification based on non-negative matrix factorization

Gene expression data classification based on non-negative ma...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chun-Hou Zheng Ping Zhang Lei Zhang Xin-Xin Liu Ju Han College of Information and Communication Technology Qufu Normal University Rizhao Shandong China Intelligent Computing Laboratory Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Institute of automation Qufu Normal University Rizhao Shandong China Biometric Research Center Department of Computing Hong Kong Polytechnic University Hong Kong China Department of Control Engineering Academy of Armored Forces Engineering Beijing China

With the advent of DNA microarrays, it is now possible to use the microarrays data for tumor classification. Yet previous works have not use the nonnegative information of gene expression data. In this paper, we propose a new method for tumor classification using gene expression data. In this method, we first select genes using nonnegative matrix factorization (NMF) and sparse NMF (SNMF). Then we extract features of the selected gene data by virtue of NMF and SNMF. At last, support vector machines (SVM) was applied to classify the tumor samples based on the extracted features. To better fit for classification aim, a modified SNMF algorithm is also proposed. The experimental results on three microarray datasets show that the method is efficient and feasible.

关键词： Gene expression Principal component analysis Independent component analysis Neoplasms Data mining Feature extraction Data analysis Humans Bioinformatics DNA

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