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Annual Conference of Industrial Electronics Society

作者： Chengdong Yang Ancai Zhang Xinghui Zhang Zhaodong Liu Guochen Pang Jianlong Qiu Yumei Wen Shandong Shanshui Jinde Cao School of Automation Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong (Linyi University) Nanjing Linyi P. R. China School of Automation and Electrical Engineering Linyi University Linyi P. R. China Shandong Shanshui Cement Group Jinan P. R. China Cement Group Jinan 250307 P. R. China Southeast University Nanjing Jiangsu CN

This paper deals with the problem of complex spatio-temporal networks, which is modeled by coupled partial integro-differential equations (PIDEs). A spatial proportional-integral-derivative (SPID) state-feedback controller is studied. With Laypunov direct method, a sufficient condition on synchronization of the complex PIDE network is investigated in terms of linear matrix inequality (LMIs). Finally, a numerical example shows the effectiveness of the proposed results.

关键词： Synchronization Delay effects Delays Mathematical model Neural networks Linear matrix inequalities Numerical stability

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intelligent Video Analysis-based Forest Fires Smoke Detection Algorithms

Intelligent Video Analysis-based Forest Fires Smoke Detectio...

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International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery

作者： Min Cai Xiaobo Lu Xuehui Wu Yifei Feng School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (纸本)9781509040940

In order to discover forest fire as early as possible, forest fire detection should focus on the smoke in early fire. This paper focuses on three key issues: motion segmentation, feature extraction and classifier design. Background subtraction based on visual background extractor (Vibe) is chosen to divide suspected smoke area when taking into account the accuracy and time consumption. And then do some corresponding morphological processing. Later on, various static and dynamic characteristics of smoke were extracted and different tests were done based on different feature combinations in forest fire smoke detection system. Lots of smoke detecting system only think about static features which will result in a certain degree of misjudgment. Analyzing the false positive rate and recognition rate of these experiments' results, the combination of movement direction, high-frequency energy based on wavelet transformation and compactness is selected to constitute the final recognition vectors. In addition, the continuity which is not mentioned in other researches won't be ignored in this paper. The final experimental results showed that the accuracy rate of this method for smoke detection could reach 92.7%.

关键词： Smoke detection Vibe Feature extraction Support vector machine

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Shadow lane robust detection by image signal local reconstruction

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2016年第3期9卷 89-102页

作者： Du, Mingfang Junzheng, Wang Nan, Li Duoyang, Li School of Automation Beijing Union University Beijing China State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Beijing Key Laboratory of Information Service Engineering

In order to resolve shadow interference and slow image processing speed in the visual navigation of unmanned vehicles on city roads, a new lane detection algorithm based on the Inverse Perspective Mapping(IPM) of vertical sub-image reconstruction using local bands was proposed. The lane’s IPM aerial image was obtained using the projective transformation of three-dimensional images of city roads. The ROI portion of the IPM map was decomposed and analyzed using the sym3 wavelet, and after analyzing and comparing the experimental results the first and second levels of the vertical sub images were selected for the reconstruction, compression, and removal of shadows from the original image. The Canny algorithm was proposed and adopted in order to extract the edge features of the reconstructed images according to real-time road image quality. A modified, polar angle, constraint-based, fast Hough transform was used to locate the candidate lanes. Finally, the main control point, straight-line-fitting algorithm was used to fit the final lanes, which achieved the precise location and recognition of the lane lines. The California Polytechnic lane data set, a public data platform, which is now widely used in road visual recognition fields around the world, was selected for the testing and verification of the algorithm. The results of the experiment and actual operation indicated that, despite having a storage space of approximately one tenth the size of similar algorithms, this detection algorithm effectively solves the issue of shadow removal, meets the real-time requirements of roadway image processing systems for unmanned vehicles with a recognition time of less than 20ms, and is robust. © 2016 SERSC.

关键词： Wavelet transforms

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Speech emotion recognition based on deep belief networks and wavelet packet cepstral coefficients

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International Journal of Simulation: systems, Science and Technology 2016年第28期17卷 28.1-28.5页

作者： Huang, Yongming Wu, Ao Zhang, Guobao Li, Yue School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

A wavelet packet based adaptive filter-bank construction combined with Deep Belief Network(DBN) feature learning method is proposed for speech signal processing in this paper. On this basis, a set of acoustic features are extracted for speech emotion recognition, namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC). CWPCC extends the conventional Mel-Frequency Cepstral Coefficients (MFCC) by adapting the filter-bank structure according to the decision task. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The well-trained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. Speech emotion recognition system is constructed with the feature set, DBNs feature learning structure and Support Vector Machine as classifier. Experimental results on Berlin emotional speech database show that the Coiflet Wavelet Packet is more suitable in speech emotion recognition than other acoustics features and proposed DBNs feature learning structure combined with CWPCC improve emotion recognition performance over the conventional emotion recognition method. © 2016, UK Simulation Society. All rights reserved.

关键词： Filter banks

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Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 113-120页

作者： Fei-Yue Wang Jun Jason Zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie Zhang Liuqing Yang IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology the Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver the Department of Computer Science and Engineering University of Minnesota the Qingdao Academy of Intelligent Industries (QAII) Qingdao Shandong China and SKL-MCCS CASIA the Department of Electrical and Computer Engineering Colorado State University

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of automation.

关键词： Religious buildings

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Scene-specific pedestrian detection based on parallel vision

arXiv

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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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Observer-based finite-time sliding mode control for reentry vehicle

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International Journal of intelligent Computing and Cybernetics 2015年第4期8卷 345-362页

作者： Xiangdong Liu Xiaohuan Ren Yongzhi Sheng School of Automation Beijing Institute of TechnologyKey Laboratory of Complex System Intelligent Control and DecisionMinistry of EducationBeijingPeople’s Republic of China

Purpose–The purpose of this paper is to design a disturbance observer-based finite-time global sliding mode control scheme for the attitude tracking control problem of the reentry vehicle with parameter uncertainties and ***/methodology/approach–Feedback linearization is first introduced to transform vehicle model into three independent second order uncertain *** a finite-time controller(FTC)is proposed for the nominal system on the basis of the homogeneity *** the integral sliding mode method is introduced for the vehicle with *** finite time convergence is achieved and global robustness is also assured by the combination of finite time control method and integral sliding mode ***,to improve the attitude angle tracking accuracy a novel finite time disturbance observer(DO)is ***–Simulation is made for the reentry vehicle with disturbances *** the results show the finite-time convergence,tracking accuracy and robustness of the proposed ***/value–The proposed control strategy has three *** of all it can achieve finite time convergence and avoid ***,it can also realize global ***,a new kind of DO is introduced to improve the tracking accuracy.

关键词： Nonlinear control Robust control Variable structure control

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How to “STEAM” Children at Home? Let Children “STEAM” Themselves

How to “STEAM” Children at Home? Let Children “STEAM” Th...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xiaoyan Gong The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

In this article, I would like to share my daughter's experience on self-STEAM education. In our daily life, she can always find problems and then dream them with her imagination, finally narrows down her solutions to solve problems in her own way. During these problem-solving processes, I noticed that she went through sciences, technology, engineering, arts and mathematics in a very natural way. So I would like to say, STEAM is the way we learn and grow ever since we were born. But later at school, we are trained in a way that subjects are completely disconnected. It might take time to change this situation at school, but at home, as parents, we need to realize that children can discover new things by themselves even from young ages, and provide rich learning environment for them and let them "STEAM " themselves in their own way.

关键词： STEM STEAM education maker education

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Multi-platform Maneuvering Target Tracking based on BLUE- AIMM- CI Algorithm 34

Multi-platform Maneuvering Target Tracking based on BLUE- AI...

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第三十四届中国控制会议

作者： Wang Mao-zhang BAI Yong-qiang Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781467374439

With the battlefield environment becomes more complicated nowadays, it's difficult to achieve high precision target tracking only using single platform of target tracking system. Especially for maneuvering targets, the application of interactive multiple model(IMM) algorithm based on a variety model becomes necessary and feasible. At the same time, the best linear unbiased estimate(BLUE) filter is much more appropriate and useful than Kalman filter when it comes to deal with nonlinear system. Most of the time, we are blind to the correlation degree of our target during the merge process of tracking. We can track our target with multi-platform with introduction of Cross-Correlation(CI) fusion algorithm which is based on distributed data and proves its effectiveness by simulation.

关键词： Multi-platform,Maneuvering target tracking,BLUE filter,AIMM,CI fusion

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A Novel Fast Haze Removal Technique for Single Image Using Image Pyramid 34

A Novel Fast Haze Removal Technique for Single Image Using I...

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第三十四届中国控制会议

作者： ZHAO Dong BAI Yong-qiang Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781467374439

Fast single image dehazing has been a challenging problem in many fields, such as computer vision and real-time applications. Recently, many dehazing algorithms have been proposed based on the dark channel prior(DCP). However, these algorithms aim to improve the refinement of the raw transmission map, while ignore the computational complexity of DCP ***, this paper proposes a new technique for fast single image haze removal, which achieves a good tradeoff between the dehazing performance and the computational complexity. We first decompose the observed haze image into a coarse image and a detail image using Gaussian-Laplacian pyramid. Then, the coarse image is dehazed by Dark Channel Prior and Guided filter(GDCP). For the size of the coarse image is 1/4 of the original image, the computational complexity is reduced ***, the recomposed image is blurred, since the detail image is still haze. So, we employ an unsharp filter to sharpen the blurred recomposed image. Experimental results show that the proposed dehazing technique effectively removes haze, and significantly reduces the computational complexity by 69.59% on average, compared with traditional GDCP algorithm.

关键词： single image dehazing,image restoration,dark channel prior,image pyramid,unsharp masking

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