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Chinese control Conference (CCC)

作者： Shang-Bin Jiao Di Sun Ding Liu Wei Chao Huang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this paper, the weak signal detection under α stable noise is investigated based on bistable vibrational resonance (VR) which is driven by a high frequency signal. On the one hand, the energy of the high frequency drive signal is transferred to the low frequency weak signal when VR occurs; on the other hand, the control of stochastic resonance (SR) is achieved based on VR, which transfers more noise energy into useful signal energy. In addition, considering the requirements of real-time detection, the amplitude and frequency of the high frequency drive signal are optimized by the knowledge-based particle swarm optimization (KPSO), which takes the mean signal-noise-ratio (MSNR) of output as the fitness function, and the property that VR system produces the best resonance effect just when the valid system parameter â(B,Ω) is greater than zero as knowledge. Finally, the parameter compensation is combined to achieve multi-high frequency weak signals detection with a stable noise. Furthermore, the method is applied to the vibration fault diagnosis of a mono-crystalline silicon furnace, and the experiment results show the effectiveness and practicability of the method.

关键词： Decision support systems

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Stochastic resonance of asymmetric bistable system driven by binary signals under α stable noise

Stochastic resonance of asymmetric bistable system driven by...

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Chinese control Conference (CCC)

作者： Shang-Bin Jiao Jie Kou Ding Liu Qing Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this paper the asymmetric bistable system excited by binary aperiodic signals is taken as a model and the average symbol error rate is regarded as an index to study stochastic resonance (SR) phenomenon. Firstly, the SR driven by binary signals under α stable noise is studied. Secondly, the interplay between the α stable noise parameters α, β, and the system parameters a, b, r on the resonant output effect is explored. The results show that weak binary signals detection can be realized by adjusting the system parameters a, b and r. The optimal values solved by these parameters can make the system produce the best SR effect. For a certain a or b, there is an optimal value under different α or β. For the parameter r, there is an optimal value under different α, and there are several optimal values under different β. Moreover, when α or β is given different values, the evolution laws in asymmetric bistable SR system excited by binary signals are same. The results lay a foundation for realizing the adaptive parameter adjustment in asymmetric bistable SR system with α stable noise.

关键词： Error analysis Signal detection Indexes Time-domain analysis Stochastic resonance Fluctuations Market research

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A novel method for the construction of evolutionary tree based on expectation maximization algorithm

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3799-3803页

作者： Chen, Zhihua Zhao, Yang Wang, Zhuo Kou, Zheng Li, Hanggao Key Lab. of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei430074 China Institute of Biomedical and Pharmaceutical Sciences College of Biological Engineering and Food Science Hubei University of Technology Wuhan Hubei430068 China College of Computer Science South-Central University for Nationalities Wuhan Hubei430074 China

The difference of protein sequence or protein structure can be used for the construction of molecular evolutionary tree or phytogenetic tree with certain hierarchy and topology. The divergent points in the tree suggest that new genes appeared or common ancestors varied. The lengths of the branch in the tree show the evolution distances between proteins when divergences happened. The analysis of protein evolution can propose some methods for molecular evolution of various species and can confirm the accurate status in the evolution history. Moreover, the molecular evolution tree of proteins is a strong evidence for species classification. In the paper, the trees are constructed by the regular express of protein sequences and the expectation maximization (EM) algorithm. The proposed method in the paper can be used conveniently and can give reliable results, which benefit the biology computing and sequence analysis. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Proteins

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Two novel cellular neural networks based on mem-elements 34

Two novel cellular neural networks based on mem-elements

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34th Chinese control Conference, CCC 2015

作者： Shen, Yi Zhenzhen, Jia Xiaoping, Wang Yang, Liu School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen China

ISBN: (纸本)9789881563897

Two types of novel cellular neural networks based on mem-elements are proposed, namely, MC-CNN and EM-CNN. The MC-CNN lets a memcapacitor replace the conventional linear capacitor of a cellular neural network cell. This improvement takes advantage of the nanoscale of memcapacitor and its natural nonlinearity, which makes the MC-CNN more compact and the output function simplified. Mathematical analysis of stability and simulation of image processing is presented to verify the feasibility and performance of MC-CNN. The EM-CNN is an economical improvement of the memristor synapse cellular neural network. In the EM-CNN, based on the symmetry of CNN templates, the amount of memristors and voltage-controlled current source is largely reduced. Thus, the EM-CNN is not only economical on the fabricating cost of CNN but also possesses a simpler cell structure which is beneficial to better implementation of CNN. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Cellular Neural Network image processing Memcapacitor Memristor

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DeNet: An explicit distance ensemble model for person re-identification

DeNet: An explicit distance ensemble model for person re-ide...

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Asian Conference on Pattern Recognition (ACPR)

作者： Jin Wang Changxin Gao Jing Hu Nong Sang Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781479961016

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets.

关键词： image color analysis Feature extraction Histograms Cameras Probes Neurons Linear programming

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Event-based synchronisation of linear discrete-time dynamical networks

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IET control Theory and Applications 2015年第5期9卷 755-765页

作者： Chen, Michael Z.Q. Zhang, Liangyin Su, Housheng Li, Chanying Department of Mechanical Engineering University of Hong Kong Hong Kong School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science andTechnology Luoyu Road 1037 Wuhan430074 China National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of Sciences Beijing100090 China

This study investigates the problem of event-based synchronisation of linear discrete-time dynamical networks. Leader-following and leaderless synchronisations are achieved by a distributed event-trigger strategy. It is shown that feedback control updating is unnecessary until an event is triggered. The combinational-state variables and the Riccati equation are used to construct a Liapunov function and to design the event-triggering conditions. Numerical examples are provided to illustrate the theoretical results. © The Institution of Engineering and Technology 2015.

关键词： Riccati equations

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Object rough localization of tongue images via clustering and gray projection

Object rough localization of tongue images via clustering an...

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2016年土木、建筑与环境工程国际学术会议

作者： Weixia Liu Zuchang Zhang Yeyu Lin Danying Shen Zuoyong Li Straits Institute Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University)

ISBN: (纸本)9781138065840

Tongue diagnosis is one of the most important diagnosis methods in Traditional Chinese Medicine(TCM).Tongue image segmentation is a crucial step in developing automatic tongue diagnosis *** localization of tongue body is a useful preprocessing step in tongue image segmentation,which can eliminate the adverse effect of strong edges from neighboring tissues such as face and lip when extracting tongue body *** exploring the existing tongue rough localization method based on gray projection,we propose a modified method combining clustering with gray projecting in this *** proposed method first conducts clustering on image pixels' hue components in HSI(Hue,Saturation and Intensity) space to seek multiple ***,image thresholding and morphological operations are conducted to generate a binary image,and the largest object region is taken as the initial localization ***,the localization result is refined by gray projection on pixels' red *** results on a variety of tongue images show that the proposed method significantly improves the accuracy of tongue rough localization in comparison with the existing gray projection method.

关键词： image Object rough localization of tongue images via clustering and gray projection

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Suspicious face detection based on key frame recognition under surveillance video

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9712 LNCS卷 645-652页

作者： Zheng, Xiaohui Ning, Yi Chen, Xianjun Zhan, Yongsong Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9783319409993

Surveillance video is characterized by large amount of data and redundancy, which makes the suspicious face detection to be a problem. To solve the problem above we proposed suspicious face detection based on key frame. Surveillance video has the type of fixed background, so this paper used the frame difference method with low computational complexity and small computation to extract the key frame. We proposed a new method combined DPM with skin color detection to detect the suspicious face in the key frames. To solve the speed bottleneck of the traditional DPM, we proposed to use the fast HOG LUT feature extraction and the near optimal cost sensitive decision making improving the traditional method. Meanwhile we used YCrCb + otsu skin color segmentation. Since the otsu is easily affected by the illumination, we proposed an improved skin color detection. Experiment results show that the proposed algorithms are robust and accurate for real-time. © Springer International Publishing Switzerland 2016.

关键词： Face recognition

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Simulation and analysis of classification optimization model of temperature sensing big data in intelligent building 2016

Simulation and analysis of classification optimization model...

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3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016

作者： Zhang, Fuquan Mao, Zijing Ding, Gangyi School of software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States School of software Beijing Institute of TechnologyBeijing 10008 1 China Software Building Beijing Institute of Technology 5 South Zhongguancun Street Haidian Beijing100081 China

ISBN: (纸本)9781450341295

The temperature sensor network in intelligent building classified collection of big data processing has the problem of big data redundancy interference, which results in unable to determine the fixed filter thresholds. This paper proposed Chaos differential disturbance based fuzzy C-means clustering model for big temperature sensing data classification tasks. It requires to analyze temperature sensor in the intelligent building big distributed structure model of data in a database storage system, the big data information flow feature fusion and time series analysis. Based on traditional fuzzy c-means clustering processing, we introduced chaos disturbance to avoid the classification into local convergence and local optimum, and therefore improve the performance of data clustering. The testing results show that our proposed classification method effectively reduces the error rate for classification tasks of temperature data in intelligent building and have achieved the best performance among the existing algorithms. © 2016 ACM.

关键词： Temperature sensors

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Bi-Channel Memristor Memory:A Design Methodology Based on Current Feedback

Bi-Channel Memristor Memory:A Design Methodology Based on Cu...

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第三十四届中国控制会议

作者： LI Wei SHEN Yi WU Jisheng School of Automation Huazhong university of Science and Technology College of Computer Science South-central university for nationalities Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong university of Science and Technology

ISBN: (纸本)9781467374439

In memristor memory design,it is often concentrated on the feedback control effect and not much on the reliability and *** study adopt an adaptive write,read and erase method,and realize a more resilient memory operation in the face of low yield in the nano-memory technology *** analyzing writing,reading and erasing strategies for our target memory cell,we present simulation results that show the feasibility of these writing,reading and erasing ***,the narrow current pulse stimulus is compared to the ramp current stimulus,and the latter one is shown to have a faster writing *** simulation results are based on a SPICE model built upon the TiO2 memristive device made in HP laboratory.

关键词： Memristor memory current teedback bi-channel

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