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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Xiaochen Li Wenji Mao Daniel Zeng Fei-Yue Wang The Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Management Information Systems University of Arizona Tucson Tucson AZ USA

ISBN: (纸本)9781424464449

Terrorism organizations are devising increasingly sophisticated plans to conduct attacks. The ability of emulating or constructing attack plans by potential terrorists can help us understand the intents and motivation behind terrorism activities. A feasible computational method to construct plans is planning technique in AI. Traditionally, AI planning methods rely on a predefined domain theory which is compiled by domain experts manually. To facilitate domain theory construction and plan generation, we propose a method to construct domain theory automatically from free text data. The effectiveness of our proposed approach is evaluated empirically through experimental studies using real world terrorist plans .

关键词： Terrorism Artificial intelligence Data mining Couplings Laboratories Intelligent systems automation management information systems Informatics Computational intelligence

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Nonlinear Model Predictive control with the Integration of Support Vector Machine and Extremal optimization

Nonlinear Model Predictive Control with the Integration of S...

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The 8th World Congress on Intelligent control and automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Peng Chen Yong-Zai Lu Department of Automation Shanghai Jiaotong University Shanghai 200240 P.R.China State Key Laboratory of Industrial Control Technology & Institute of Cyber-Systems and Control Zheji

In nonlinear model predictive control (NMPC), the system performance is greatly dependent upon the accuracy of the predictive model and the efficiency of the online optimization algorithm. In this paper, a novel NMPC scheme with the integration of Support Vector Machine (SVM) and recently proposed general-purpose heuristic “Extremal Optimization (EO)” is presented. With the superior features of self-organized criticality (SOC), non-equilibrium dynamics, coevolutions in statistical mechanics and ecosystems respectively, a carefully designed EO based on “horizon based mutation strategy” is used as an online solver to obtain optimal future control inputs of NMPC, in which a multi-step-ahead SVM predictive model is employed. Furthermore, simulation studies on a typical nonlinear system are given to illustrate the effectiveness of the proposed control scheme.

关键词： Predictive models Optimization Support vector machines Predictive control Computational modeling Biological system modeling

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Static output feedback control of a class of complex networks

Static output feedback control of a class of complex network...

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IEEE Conference on Decision and control

作者： Pingli Lu Ying Yang School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Turbulence and Complex Systems Department of Mechanics and Aerospace Engineering Peking University Beijing China

ISBN: (纸本)9781424477456

In this paper, decentralized static output feedback is considered for a class of dynamic networks with each node being a nonlinear system with infinite equilibria. Based on the Kalman-Yakubovich-Popov (KYP) lemma, linear matrix inequality (LMI) conditions are established to guarantee the stability of such dynamic networks. Furthermore, an interesting conclusion is reached: the stability problem for the whole Nn-dimensional dynamic networks can be converted into the simple n-dimensional space in terms of only two LMIs. A concrete application of output stabilization of coupled phase-locked loop networks is used to verify the effectiveness of the proposed methods.

关键词： Linear matrix inequalities Phase locked loops Stability analysis Output feedback Nonlinear dynamical systems Symmetric matrices

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Multi-targets tracking based on SB/MHT theory

Multi-targets tracking based on SB/MHT theory

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作者： Ru, Qi Peng, Zhihong Zhang, Juan Chen, Xun School of Automation Beijing Institute of Technology Beijing 100081 China Education Ministry Key Laboratory of Intelligent Control of Complex Systems and Decision Beijing 100081 China

ISBN: (纸本)9787894631046

Multi-targets video tracking theory is introduced briefly, and the structured Branching MHT algorithm is applied in Multi-targets video tracking system. Connected with Kalman filter, hypotheses are built by SB/MHT using measures which are stretched by Bhattacharyya coefficient. In this way, Multi-targets video tracking can carry out. Feasibility of this method is validated by simulation.

关键词： Kalman filters

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Delayed-state-feedback Exponential Stabilization of Stochastic Markovian Jump systems with Mode-dependent Time-varying state Delays

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Acta Automatica Sinica 2010年第11期36卷 1601-1610页

作者： Li MA Fei-Peng DA Ling-Yao WU Key Laboratory of Measurement and Control for Complex Systems of Engineering Ministry of Education Research Institute of Automation Southeast University Nanjing 210096 P.R. China College of Electronic and Information Engineering Jiangsu University Zhenjiang 212013 P.R. China

Abstract In this paper, an improved mean-square exponential stability condition and delayed-state-feedback controller for stochastic Markovian jump systems with mode-dependent time-varying state delays are obtained. First, by constructing a modified Lyapunov-Krasovskii functional, a mean-square exponential stability condition for the above systems is presented in terms of linear matrix inequalities (LMIs). Here, the decay rate can be a finite positive constant in a range and the derivative of time-varying delays is only required to have an upper bound which is not required to be less than 1. Then, based on the proposed stability condition, a delayed-state-feedback controller is designed. Finally, numerical examples are presented to illustrate the effectiveness of the theoretical results.

关键词： Stochastic systems time-varying delay exponential stability Markov chain

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Analysis of neural interaction in motor cortex during reach-to-grasp task based on Dynamic Bayesian Networks

Analysis of neural interaction in motor cortex during reach-...

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

作者： Dong Sang Bin Lv Huiguang He Jiping He Feiyue Wang Key Laboratory of Complex Systems and Intelligent Science Institute of Automation Chinese Academy and Sciences Beijing China Harrington Department of Bioengineering and the Center of Neural Interface Design Arizona State University Tempe USA

In this work, we took the analysis of neural interaction based on the data recorded from the motor cortex of a monkey, when it was trained to complete multi-targets reach-to-grasp tasks. As a recently proved effective tool, Dynamic Bayesian Network (DBN) was applied to model and infer interactions of dependence between neurons. In the results, the gained networks of neural interactions, which correspond to different tasks with different directions and orientations, indicated that the target information was not encoded in simple ways by neuronal networks. We also explored the difference of neural interactions between delayed period and peri-movement period during reach-to-grasp task. We found that the motor control process always led to relatively more complex neural interaction networks than the plan thinking process.

关键词： Neurons Markov processes Bayesian methods Delay Neural networks Cathode ray tubes Encoding

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Exploring Social Annotations with the Application to Web Page Recommendation

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Journal of Computer Science & Technology 2009年第6期24卷 1028-1034页

作者：李慧倩夏粉曾大军王飞跃毛文吉 Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Department of Management Information Systems University of Arizona

Collaborative social annotation systems allow users to record and share their original keywords or tag attachments to Web resources such as Web pages, photos, or videos. These annotations are a method for organizing and labeling information. They have the potential to help users navigate the Web and locate the needed resources. However, since annotations axe posted by users under no central control, there exist problems such as spare and synonymous annotations. To efficiently use annotation information to facilitate knowledge discovery from the Web, it is advantageous if we organize social annotations from semantic perspective and embed them into algorithms for knowledge discovery. This inspires the Web page recommendation with annotations, in which users and Web pages are clustered so that semantically similar items can be related. In this paper we propose four graphic models which cluster users, Web pages and annotations and recommend Web pages for given users by assigning items to the right cluster first. The algorithms are then compared to the classical collaborative filtering recommendation method on a real-world data set. Our result indicates that the graphic models provide better recommendation performance and are robust to fit for the real applications.

关键词： graphic model EM （expectation-maximization） social annotation tag recommendation

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An Optimal control Scheme for a Class of Discrete-time Nonlinear systems with Time Delays Using Adaptive Dynamic Programming

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Acta Automatica Sinica 2010年第1期36卷 121-129页

作者： Qing-Lai WEI Hua-Guang ZHANG De-Rong LIU Yan ZHAO Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100190 P. R. China School of Information Science and Engineering Northeastern University Shenyang 110004 P. R. China Department of Automatic Control Engineering Shenyang Institute of Engineering Shenyang 110136 P. R. China

Abstract In this paper, an optimal control scheme for a class of nonlinear systems with time delays in both state and control variables with respect to a quadratic performance index function is proposed using a new iterative adaptive dynamic programming (ADP) algorithm. By introducing a delay matrix function, the explicit expression of the optimal control is obtained using the dynamic programming theory and the optimal control can iteratively be obtained using the adaptive critic technique. Convergence analysis is presented to prove that the performance index function can reach the optimum by the proposed method. Neural networks are used to approximate the performance index function, compute the optimal control policy, solve delay matrix function, and model the nonlinear system, respectively, for facilitating the implementation of the iterative ADP algorithm. Two examples are given to demonstrate the validity of the proposed optimal control scheme.

关键词： Adaptive dynamic programming (ADP) approximate dynamic programming time delay optimal control nonlinear system neural networks

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Performance Evaluation of Machine Learning Methods in Cultural Modeling

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Journal of Computer Science & Technology 2009年第6期24卷 1010-1017页

作者：李晓晨毛文吉曾大军苏鹏王飞跃 Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Department of Management Information Systems University of Arizona School of Management Engineering Shandong Jianzhu University

Cultural modeling （CM） is an emergent and promising research area in social computing. It aims to develop behavioral models of human groups and analyze the impact of culture factors on human group behavior using computational methods. Machine learning methods, in particular classification, play a critical role in such applications. Since various cultural-related data sets possess different characteristics, it is important to gain a computational understanding of performance characteristics of various machine learning methods. In this paper, we investigate the performance of seven representative classification algorithms using a benchmark cultural modeling data set and analyze the experimental results as to group behavior forecasting.

关键词： cultural modeling （CM） machine learning classification group behavior forecasting

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A new method for compensating phase-shifting error in phase measuring profilometry

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Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) 2010年第SUPPL. 1期40卷 302-307页

作者： Zhu, Lin Da, Feipeng Gai, Shaoyan Research Institute of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Edu. Southeast University Nanjing 210096 China

A new phase-shifting error compensating algorithm for phase-measuring profilometry is proposed. In this error detecting algorithm, it is supposed that sinusoidal fringe is projected to the plate, thus the phase differences between adjacent pixels are equal. Three adjacent phase points are taken as the research object. Combining the principle of phase compensation measurement, each phase of the point is presented as an equation containing the phase-shifting error. According to the characteristics that the phase differences between adjacent pixels are equal, an equation to calculate the phase-shifting error is constructed. Then the phase shifting error is taken into account in the original algorithm for error compensation. Simulation results show the inhibitory effect of the error compensation by using the novel algorithm. The proposed algorithm is also used for three-dimensional reconstruction. The final result shows that the new compensation algorithm is better than the original one obviously. This error compensating algorithm can effectively improve the accuracy of three-dimensional measurement.

关键词： Error compensation

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