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第35届中国控制会议

作者： WANG Miaomiao XIE Guo DU Jinhua Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

This paper proposes a dependency-enhanced pre-reordering method for Chinese-English statistical machine translation(SMT).Firstly,two kinds of dependency structure-based rules are extracted based on the source-side dependency tree and corresponding word alignments between the source-side and the target-side *** a maximum entropy classifier is used to calculate the orientation probability in terms of swap or monotone between two *** a result,a reordering rule set is *** different ways are proposed to filter out the rule ***,the dependency parsing trees of the training data,development set and the test set are traversed,and if the syntactic sub-tree structure matches the rules in the rule set,the word orders will be ***,a reordered source-side sentence is generated and then fed into an SMT system for *** conducted on NIST Chinese-English MT data sets show that the proposed method significantly improves translation performance by 0.46 BLEU compared to the baseline system.

关键词： Statistical Machine Translation Word Alignment Dependency Syntactic Parsing

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Robust Semi-global Coordinated Tracking of Saturated Networked systems

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IFAC-PapersOnLine 2017年第1期50卷 8303-8308页

作者： Wang X. Su H. Cai Y. Department of Automation Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China

This paper focuses on the robust semi-global coordinated tracking of general linear systems subject to input saturation together with input additive disturbance and dead zone. A fully distributed algorithm which relating only with the number of the following agents and the relative state information of its neighbors is first constructed, and then sufficient conditions guaranteeing the robust semi-global consensus tracking and the robust semi-global swarm tracking are provided, respectively, on the basis of the low-and-high feedback technique. Finally, numerical simulations are performed to illustrate the effectiveness of the theoretical results. © 2017

关键词： dead zone input additive disturbance input saturation Networked system robust coordinated tracking

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The Identification of Stochastic Time-varying Parameters for Nonlinear system 35

The Identification of Stochastic Time-varying Parameters for...

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第35届中国控制会议

作者： XIE Guo ZHANG Dan QIAN Fucai Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

In this paper, a method for a sort of nonlinear system identification with stochastic time-varying parameter is investigated. This kind of nonlinear systems is referring to the system where probability density functions(PDFs) of the parameters are known. This parameter identification and states estimation method is realized based on expectation maximization(EM) algorithm and particle filter. Firstly, parameter particles are generated randomly according to the PDF of parameter. Secondly, the particle filter is employed to estimate system states corresponding to each group of the parameters, and the weight of each group parameters is calculated according to the Bayesian theory. Then the new iteration of parameter is obtained by adopting the expectation maximization algorithm. Lastly, the real parameters are obtained along with system operation. Numerical illustrations are presented to exhibit the effectiveness of the method proposed herein, and the performance of the method is examined.

关键词： Stochastic time-varying parameter Parameter identification Nonlinear system Expectation Maximization algorithm(EM)

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Application of Case Teaching Method in Artificial Intelligence Teaching

Application of Case Teaching Method in Artificial Intelligen...

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作者： Li Huang Wei Hu Chong Tan College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology

Aiming at the current situation of poor quality of artificial intelligence teaching and weak students' interest in learning, a case teaching method is proposed. This paper analyzes the teaching status of artificial intelligence firstly, and then systematically describes the case teaching method. Finally, the necessity of introducing case teaching method into artificial intelligence teaching is studied. Practice shows that the case teaching method can effectively enhance students' self-learning ability, improve students' comprehensive innovation ability, and promote the development of artificial intelligence teaching.

关键词： Case teaching method Artificial intelligence Teaching case Course

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Reform of Computer Teaching for Practical Application

Reform of Computer Teaching for Practical Application

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作者： Li Huang Kai Zhang Wei Hu Mingchao Yu College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology

In view of the rapid development of contemporary computer technology, the problems that can be solved by computer technology are more and more complicated. Therefore, it is required that contemporary college students need to master certain computer operation skills and basic application skills of computer software combined with their professional knowledge before they officially enter the society. In this context, aiming at the computer-based teaching mode of non-computer majors in colleges and universities, the author analyzes the current situation of computer basic teaching in colleges and universities through his many years of teaching experience, and discusses the shortcomings in the development of computer courses in colleges and universities. Based on the degree of social requirements for contemporary college students to master computer technology, how to make university computer teaching cater to the continuous development and progress of computer science and technology, combined with the future computer skills of undergraduate students, the author puts forward some computer teaching reform opinions.

关键词： Computer foundation Teaching mode Application ability

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Robot Visual Sliding Mode Servoing using SIFT Features 35

Robot Visual Sliding Mode Servoing using SIFT Features

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第35届中国控制会议

作者： XIN Jing RAN Bao-jing MA Xiao-min School of Automation & Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

To solve the robot visual servoing problem in the natural scene,a robot visual sliding servoing method using SIFT features in the framework of epipolar-geometry-based visual servoing is ***,corresponding image feature points from the current image feature and the desired image are obtained by SIFT algorithm;Then the features error of the whole robot visual servoing system are calculated according to the corresponding points;Finally,considering characteristics of epipolar geometry for robot visual servoing system,the rotation sliding mode controller and translation sliding mode controller are sequentially designed to calculate the rotation movement and translation movement of the robot *** positioning experiments on a 6DOF industrial robot demonstrate that the proposed method can effectively locate an object in the natural scene.

关键词： Epipolar geometry Visual servoing Sliding mode control SIFT features

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Visual Navigation for Mobile Robot with Kinect Camera in Dynamic Environment 35

Visual Navigation for Mobile Robot with Kinect Camera in Dyn...

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第35届中国控制会议

作者： XIN Jing JIAO Xiao-liang YANG Yin LIU Ding School of Automation & Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

To solve the problem of the visual navigation for mobile robot in dynamic environment,a visual navigation system for mobile robot with Kinect camera is ***,the improved RBPF(RAO Blackwellized particle filters) algorithm is used to build the 2D grid map of the indoor environment and on the basis of this map operation of inflating obstacles is applied to build the global grid map considering the actual size of the ***,cost map using motion primitives is built while using this cost map,anytime Repairing A*(ARA*) global path planning algorithm,which has property of anytime algorithm,is combined with Dynamic Window Approach(DWA) local path planning algorithm to plan a smooth path from start point to target point and generate the optimal control input for robot ***,the adaptive monte carlo localization method(KLD-Sampling) is used to locate the robot and then a visual navigation system for mobile robot with Kinect camera is *** indoor mobile robot navigation experiment results show that the designed robot navigation system can plan a smooth path which is in accordance with robot kinematics and autonomously avoid the static and moving obstacles in the environment.

关键词： Kinect Camera Motion primitives Cost map Visual navigation Dynamic environment

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Battle damage assessment based on an improved Kullback-Leibler divergence sparse autoencoder

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Frontiers of information Technology & Electronic Engineering 2017年第12期18卷 1991-2000页

作者： Zong-feng QI Qiao-qiao LIU Jun WANG Jian-xun LI State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Luoyang 471003 China MOE Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China Luoyang Electronic Equipment Test Center of China Luoyang 471000 China

The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder （KL-SAE） is proposed in this paper, which can be applied to battle damage assessment （BDA）. This method can select automatically the hidden layer feature which contributes most to data reconstruction, and abandon the hidden layer feature which contributes least. Therefore, the structure of the network can be modified. In addition, the method can select automatically hidden layer feature without loss of the network prediction accuracy and increase the computation speed. Experiments on University ofCalifomia-Irvine （UCI） data sets and BDA for battle damage data demonstrate that the method outperforms other reference data-driven methods. The following results can be found from this paper. First, the improved KL-SAE regression network can guarantee the prediction accuracy and increase the speed of training networks and prediction. Second, the proposed network can select automatically hidden layer effective feature and modify the structure of the network by optimizing the nodes number of the hidden layer.

关键词： Battle damage assessment Improved Kullback-Leibler divergence sparse autoencoder Structural optimization Feature selection

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Modelling Transcriptional Regulation with Fractional Order Differential Equation using Gaussian Process 35

Modelling Transcriptional Regulation with Fractional Order D...

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第35届中国控制会议

作者： JI Ruirui ZHANG Xinxin YAN Xiaomei School of Automation and Information Engineering Xi'an University of Technology Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

A reasonable math model is fundamental to describing gene regulatory mechanism.A new method is proposed to model transcriptional regulation with transcription factor from gene expression profiles using fractional order differential *** Process is employed as a tool to model the latent transcription factor activity and particle swarm optimization algorithm is utilized to optimize the fractional order,kinetic parameters in the model and hyperparameters in kernel *** results of the experiment on real gene expression profiles indicate that the fractional order differential equation fits data better,also the proposed approach is feasible to model transcriptional regulation.

关键词： Transcriptional regulation Fractional order differential equation Gaussian Process Particle swarm optimization

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