检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Huang, Yi Jia, Peng Cai, Dongmei Cai, Bojun College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan030024 China Department of Physics Durham University South Road DurhamDH1 3LE United Kingdom Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan030024 China

Next-generation ground-based solar observations require good image quality metrics for post-facto processing techniques. Based on the assumption that texture features in solar images are multi-fractal which can be extracted by a trained deep neural network as feature maps, a new reduced-reference objective image quality metric, the perception evaluation is proposed. The perception evaluation is defined as cosine distance of Gram matrix between feature maps extracted from high resolution reference images and that from blurred images. We evaluate performance of the perception evaluation with simulated blurred images and real observation images. The results show that with a high resolution image as reference, the perception evaluation can give robust estimate of image quality for solar images of different scenes. Copyright © 2019, The Authors. All rights reserved.

关键词： Information management

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Solar Image Restoration with the Cycle-GAN Based on Multi-Fractal Properties of Texture Features

arXiv

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arXiv 2019年

作者： Jia, Peng Huang, Yi Cai, Bojun Cai, Dongmei College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan030024 China Department of Physics Durham University South Road DurhamDH1 3LE United Kingdom Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan030024 China

Texture is one of the most obvious characteristics in solar images and it is normally described by texture features. Because textures from solar images of the same wavelength are similar, we assume texture features of solar images are multi-fractals. Based on this assumption, we propose a pure data-based image restoration method: with several high resolution solar images as references, we use the Cycle-Consistent Adversarial Network to restore burred images of the same steady physical process, in the same wavelength obtained by the same telescope. We test our method with simulated and real observation data and find that our method can improve the spatial resolution of solar images, without loss of any frames. Because our method does not need paired training set or additional instruments, it can be used as a post-processing method for solar images obtained by either seeing limited telescopes or telescopes with ground layer adaptive optic system. Copyright © 2019, The Authors. All rights reserved.

关键词： Image reconstruction

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Exponential Stability of Highly Nonlinear Neutral Stochastic Differential Delay Equations

Exponential Stability of Highly Nonlinear Neutral Stochastic...

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Chinese control Conference (CCC)

作者： Yinghui Hu Xiaofeng Zong Jinhua She Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

This paper investigates the mean square and almost sure stability of a class of neutral stochastic differential delay equations with highly nonlinear coefficients. We first examine the regularity of the solution to the highly nonlinear neutral stochastic differential delay systems. Then the explicit stability conditions are obtained by the Lyapunov functional and semi-martingale convergence theorem. Especially, the explicit stability conditions of pure delay neutral stochastic differential delay equations are obtained. It is revealed that the delay term in the drift can contribute to the mean square and almost sure stability.

关键词： Stability criteria Delays Asymptotic stability control theory Differential equations

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Design and Application of a Web-based Comprehensive Evaluation and Decision Support System for Tobacco Cultivation Process

Design and Application of a Web-based Comprehensive Evaluati...

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第37届中国控制会议

作者： Gong Chen Yonghua Xiong Wei Chen Hao Zhou School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Guizhou Tobacco Science Institute

The evaluation and decision support system are widely used in agriculture with the development of information technology. In this paper, a Web-based comprehensive evaluation and decision support system（WCEDSS） is designed for flue-cured tobacco cultivation process. Using the artificial neural networks and some image processing methods, WCEDSS can predict various indicators of tobacco such as yield and flue-cured score, or give decisions at different stages of tobacco cultivation. As the system is developed by the Browser/Server（B/S） architecture, it is possible to make full use of the Internet resources and to facilitate users at any place with access to the Internet. Test results indicates that WCEDSS can achieve good performance. With other auxiliary functions, the system shows potential and extensive practicality in agricultural information management and guidance.

关键词： tobacco Browser/Server architecture evaluate decision support

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Design of High-Gain-Observer-Based State Feedback controller for Positive Time-Delay System

Design of High-Gain-Observer-Based State Feedback Controller...

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Chinese control Conference

作者： Mingyuan Xie Jinhua She Zhentao Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

This paper investigates the stabilizability of positive time-delay system. The nonnegative constraint makes the design of a control law different from a general system. Firstly, a method to calculate the L_1 gain of a positive time-delay system is presented. Then, the design of a state feedback controller and a high-gain observer is presented by taking full advantage of the characteristics of the positiveness of the system. Finally, the observer and feedback controller are combined to stabilize the system and improve dynamic performance. A numerical example illustrates the provided method is effective.

关键词： Observers State feedback Delays Closed loop systems Adaptive control Delay effects

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Hierarchical Prediction Model Based on BP Neural Network for Predicting CO/CO_2 in Iron Ore Sintering Process

Hierarchical Prediction Model Based on BP Neural Network for...

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Chinese control Conference

作者： Ben Xu Xin Chen Yang Zhou School of Automation China University of Geosciences Wuhan China Intelligent Automation for Complex Systems Hubei key Laboratory of Advanced Control Wuhan China

The sintering process is one of the most energy-consuming processes in steelmaking, its carbon fuel consumption accounts for 8% to 10% in the steel production process. To find ways of reducing the energy consumption, it is necessary to predict the carbon efficiency. The value of CO/CO_2 in the carbon emission can reflect the utilization of carbon combustion in sintering process. In this study, the CO/CO_2 is taken to be a measure of carbon efficiency and a hierarchical model is built to predict it. Firstly, the physical and chemical reactions and the carbon flow mechanism in the sintering process are analyzed, and the process parameters that affect the CO/CO_2 are determined. Then, the gray relational analysis method is used to analyze the influence factors to determine the relationship between the parameters, and a hierarchical predictive model for CO/CO_2 is established based on the relationship between the parameters. The hierarchical predictive model is divided into two parts: the predictive models for the thermal state parameters and the predictive model for CO/CO_2. The inputs of the predictive models for the thermal state parameters are the raw material parameters and the operating parameters, and the inputs of the predictive model for CO/CO_2 are the predicted values of the predictive models for the thermal state parameters. Finally, the simulation results verify the effectiveness of the proposed modeling method. This method can provide a theoretical basis for the optimization and control of carbon efficiency in the sintering process.

关键词： Predictive models Combustion Correlation Mathematical model Carbon dioxide Chemicals Raw materials

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Gesture Intention Understanding Based on Depth and RGB Data

Gesture Intention Understanding Based on Depth and RGB Data

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Chinese control Conference

作者： Yu Feng Luefeng Chen Wanjuan Su Kaoru Hirota Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo Institute of Technology Yokohama Japan

Aiming at the problem that the process of gesture recognition based on color image is greatly affected by environmental factors such as lighting, a gesture intent understanding method based on the fusion of Red-Green-Blue (RGB) data and depth data is proposed. Firstly, the gesture feature extraction based on the Speeded Up Robust Feature (SURF) method after foreground segmentation are used to get gesture information. Then, we apply Backpropagation (BP) neural network to classify and recognize gestures. The final recognition results are obtained through data fusion from recognition results based on both RGB images and depth images. We evaluated the effectiveness of the proposed method through ChaLearn Gesture Database.

关键词： Feature extraction Image segmentation Gesture recognition Robustness Image recognition Neural networks Robot sensing systems

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Street Object Detection Based on Faster R-CNN

Street Object Detection Based on Faster R-CNN

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第37届中国控制会议

作者： Wendi Cai Jiadie Li Zhongzhao Xie Tao Zhao Kang Lu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Library of Wuhan University of Technology

With the increased number of traffic accidents, the research and development of smart cars have been *** detection of street objects has become one of the important research topics. Generic Model detection algorithm based on Convolution Neural Network(CNN) need to design the training model, while the training and testing of the model will take a lot of time. Transfer Learning is used to fine-tune the pre-trained models, using the Image task datasets of COCO, transferring a generic deep learning model to specific one with different weights and outputs. Furthermore, the CNN structure is adjusted to improve overall performance, and the street environment is trained to the special scene. We compare the results of experiments,and the results showed that the network which is fine-tuned is effective.

关键词： Transfer Learning Faster R-CNN Inception-ResNet-v2 Object Detection

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Modeling and Maximizing Angle Coverage in Visual Sensor Networks

Modeling and Maximizing Angle Coverage in Visual Sensor Netw...

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第37届中国控制会议

作者： Yonghua Xiong Manjie Lu Wei Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Guizhou Tobacco Science Institute

Maintaining the quality of network coverage is a major concern in visual sensor networks. In this paper, we study the angle coverage problem in visual sensor networks, considering the target is very large, and each camera node can only monitor a portion of its perimeter. The goal of the proposed work is to schedule camera nodes to achieve maximum angle coverage in different period. Firstly, we establish a novel coverage model and formally prove that the problem is NP-hard in ***, we present a scheduling scheme based on greedy algorithm, to schedule camera nodes into disjoint cover sets working in ***, we conclude that the approximate ratio of the proposed algorithm is k, theoretically, and the time complexity of the algorithm is O（n）. Finally, extensive simulations have been conducted to evaluate the performance of the proposed algorithm.

关键词： Visual sensor network angle coverage camera node scheduling greedy algorithm

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control of Wireless Network Communication for Industrial Robot Servo systems

Control of Wireless Network Communication for Industrial Rob...

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Chinese control Conference (CCC)

作者： Meiliu Li Guangjun Wang Jinhua She Zhentao Liu Danyun Li Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

To meet the needs of high speed and good environmental adaptability for data transmission in industrial robot servo systems, this paper presents a wireless transmission technology on a data acquisition control terminal. The system is based on STM32F103RET6 processor and reads cache data from the SRAM of FPGA in DMA method, and communicates with a WIFI chip, Marvell 88w8686, through the SDIO interface. A host computer segments and filters the data received by the WIFI chip and sends control commands back to STM32. The functions of the hardware and software of the system contains data compression and storage, wireless data transmission, data display, and control-command transmission. An experimental platform has been built. It carries out real-time transmission of 8-16 digits based on the TCP/IP protocol with expected performance.

关键词： Wireless fidelity Wireless communication Servomotors Data communication Service robots Field programmable gate arrays

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