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2017 International Conference on Computer Technology, Electronics and Communication, ICCTEC 2017

作者： Ren, Hui Li, Shuwei Sun, Rongshu Su, Zhibin School of Information Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing Key Laboratory of Modern Entertainment Technology Beijing100024 China

ISBN: (纸本)9781538657843

Aiming at overcoming the defects of basic lighting color rendering for LED stage lighting, this paper establishes a new mixing light method with RGBW four-color mixing model. Compared with traditional tricolor light mixing model, it uses the mixing light of white as the fourth input, with the threebasic color of red, green and blue to obtain a new mixing method. Then the original coefficients of RGBW are optimized after adjusting the two parameters of relative spectral power distribution and illuminance of mixing light for locus fitting of blackbody. Finally, better color rendering of white light can be acquired. By the MATLAB simulation and field testing, experimental results have shown that the proposed method will achieve ideal LED lighting performance, which is convenient for color management of lighting control system in modern theatre. © 2017 IEEE.

关键词： Light emitting diodes

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Single image super-resolution via cascaded multi-scale cross network

arXiv

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arXiv 2018年

作者： Hu, Yanting Gao, Xinbo Li, Jie Huang, Yuanfei Wang, Hanzi Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xian710071 China State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xian710071 China Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University China

The deep convolutional neural networks have achieved significant improvements in accuracy and speed for single image super-resolution. However, as the depth of network grows, the information flow is weakened and the training becomes harder and harder. On the other hand, most of the models adopt a single-stream structure with which integrating complementary contextual information under different receptive fields is difficult. To improve information flow and to capture sufficient knowledge for reconstructing the high-frequency details, we propose a cascaded multi-scale cross network (CMSC) in which a sequence of subnetworks is cascaded to infer high resolution features in a coarse-to-fine manner. In each cascaded subnetwork, we stack multiple multi-scale cross (MSC) modules to fuse complementary multi-scale information in an efficient way as well as to improve information flow across the layers. Meanwhile, by introducing residual-features learning in each stage, the relative information between high-resolution and low-resolution features is fully utilized to further boost reconstruction performance. We train the proposed network with cascaded-supervision and then assemble the intermediate predictions of the cascade to achieve high quality image reconstruction. Extensive quantitative and qualitative evaluations on benchmark datasets illustrate the superiority of our proposed method over state-of-the-art super-resolution methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep neural networks

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A novel fault classification method based on neural network in smart grid

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International Journal of Electrical Engineering 2018年第1期25卷 1-7页

作者： Zhang, Tong Sun, Lanxiang Liu, Jianchang Yu, Haibin College of Information Science and Engineering Northeastern University Shenyang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control System CAS Shenyang China University of Chinese Academy of Sciences Beijing China

This paper presents a back propagation (BP) neural network method to identify fault types and phases in the smart grid with renewable sources. A fault classification method based on the BP neural network is used to identify patterns of voltage and current measured with phasor measurement unit (PMU). The voltage and current values are decomposed, and then they are used as the input matrix of the BP neural network, which identifies the fault type and fault phasor. All the common short-circuit faults occurred are analyzed, BP neural network method is proposed for fault classification in a power active distribution network. Simulation results show feasibility and usefulness of the BP neural network method, which provides good classification performances.

关键词： Smart power grids

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Automatic coregistration for multiview SAR images in urban areas

Automatic coregistration for multiview SAR images in urban a...

引用

ISPRS Geospatial Week 2017

作者： Xiang, Yuming Kang, Wenchao Wang, Feng You, Hongjian Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

关键词： Synthetic aperture radar

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A novel and fast corner detection method for SAR imagery

A novel and fast corner detection method for SAR imagery

引用

ISPRS Geospatial Week 2017

作者： Jiao, Niangang Kang, Wenchao Xiang, Yuming You, Hongjian Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Corners play an important role on image processing, while it is difficult to detect reliable and repeatable corners in SAR images due to the complex property of SAR sensors. In this paper, we propose a fast and novel corner detection method for SAR imagery. First, a local processing window is constructed for each point. We use the local mean of a 3 × 3 mask to represent a single point, which is weighted by a Gaussian template. Then the candidate point is compared with 16 surrounding points in the processing window. Considering the multiplicative property of speckle noise, the similarity measure between the center point and the surrounding points is calculated by the ratio of their local means. If there exist more than M continuous points are different from the center point, then the candidate point is labelled as a corner point. Finally, a selection strategy is implemented by ranking the corner score and employing the non-maxima suppression method. Extreme situations such as isolated bright points are also removed. Experimental results on both simulated and real-world SAR images show that the proposed detector has a high repeatability and a low localization error, compared with other state-of-the-art detectors.

关键词： Synthetic aperture radar

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Extending signal temporal logic specifications for distributed model predictive control

Extending signal temporal logic specifications for distribut...

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Asian control Conference

作者： Linli Zhang Dewei Li Yugeng Xi Jiwei Li Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai CN

ISBN: (纸本)9781509015740;9781509015733

In recent years, model predictive control with signal temporal logic (STL) propositions serving as the constraints has become an emerging research area. In this paper, we extend STL to specify the behaviors of both controlled systems and controllers in the distributed model predictive control (DMPC) framework. The proposed design aims to specify desired properties and satisfy correctness requirements. To obtain optimal controllers and expected properties, we encode an auto-programming to combine the system dynamics and the STL constraints into a mixed-integer linear/quadratic programming (MILP/MIQP) optimization problem. What's more, the experimental results for controllers of multi-tank liquid-level control systems are presented to verify the correctness of this procedure.

关键词： Optimization Predictive control Semantics control systems Prediction algorithms Discrete-time systems Syntactics

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Enhanced Exergy Cost Optimization of Operating Conditions in FCCU Main Fractionator

Enhanced Exergy Cost Optimization of Operating Conditions in...

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第28届中国过程控制会议（CPCC 2017）暨纪念中国过程控制会议30周年

作者： ZHONG Chonglin ZHENG Yi LI Shaoyuan Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education

Exergy indicates the maximal energy that can do work *** from the limited optimization of product quality or the calculation of generic energy conservation in most previous studies,the application of exergy analysis and exergy cost optimization in petrochemical industry is of great economic and environmental *** on the FCCU main fractionator in Jiujiang Petrochemical Complex No.2 FCCU,an enhanced exergy cost optimization under different operating conditions by adjusting set points of temperature and valves opening degree for flow control are studied in this paper in order to reduce exergy cost and improve the quality of energy.A steady-state optimization algorithm to enhance exergy availability and an objective function comprehensively considering exergy loss are *** the basis of ensuring the quality of petroleum products,the economic benefits can be improved by optimizing the controllable variables due to the fact that exergy cost is decreased.

关键词： Exergy Optimization of Operating Conditions Fractionator FCCU Exergy Cost

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Position detection and direction prediction for arbitrary-oriented ships via multiscale rotation region convolutional neural network

arXiv

引用

arXiv 2018年

作者： Fu, Kun Guo, Zhi Yan, Menglong Sun, Xian Sun, Hao Yang, Xue Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

—Ship detection is of great importance and full of challenges in the field of remote sensing. The complexity of application scenarios, the redundancy of detection region, and the difficulty of dense ship detection are all the main obstacles that limit the successful operation of traditional methods in ship detection. In this paper, we propose a brand new detection model based on multiscale rotational region convolutional neural network to solve the problems above. This model is mainly consist of five consecutive parts: Dense Feature Pyramid Network (DFPN), adaptive region of interest (ROI) Align, rotational bounding box regression, prow direction prediction and rotational nonmaximum suppression (R-NMS). First of all, the low-level location information and high-level semantic information are fully utilized through multiscale feature networks. Then, we design adaptive ROI Align to obtain high quality proposals which remain complete spatial and semantic information. Unlike most previous approaches, the prediction obtained by our method is the minimum bounding rectangle of the object with less redundant regions. Therefore, rotational region detection framework is more suitable to detect the dense object than traditional detection model. Additionally, we can find the berthing and sailing direction of ship through prediction. A detailed evaluation based on SRSS and DOTA dataset for rotation detection shows that our detection method has a competitive performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Remote sensing

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Model and Algorithms for Competitiveness Maximization on Complex Networks

引用

IFAC-PapersOnLine 2017年第1期50卷 9438-9443页

作者： Zhao J. Liu Q. Wang L. Wang X. Chen G. Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Institute of Complexity Science Qingdao University Qingdao China Department of Electronic Engineering City University of Hong Kong Hong Kong Hong Kong

In this paper we study a competition model on complex networks, where two competing agents are fixed to different states while other agents are evolving to update their states through interactions according to a distributed consensus rule. We consider the situation where one competitor has the opportunity to add new links to other evolving agents such that it could improve its influence on the number of its supporters. We focus on the problem of how to add these new links in order to maximize the influence of a competitor against its rival, referred to as competitiveness. We formulate this competition as a competitiveness maximization problem, which tries to maximize the number of supports of a given competitor against its rival. We analyze the properties of this problem on some special graphs and provide optimal solutions for them, respectively. We design a simulated annealing algorithm and three heuristic algorithms to approximately solve this NP-hard constrained optimization problem. © 2017

关键词： Competitive dynamics complex network heuristic algorithm simulated annealing algorithm

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Wider channel attention network for remote sensing image super-resolution

arXiv

引用

arXiv 2018年

作者： Gu, Jun Xu, Guangluan Zhang, Yue Sun, Xian Wen, Ran Wang, Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods treat low-resolution (LR) inputs and features equally across channels, rarely notice the loss of information flow caused by the activation function and fail to leverage the representation ability of CNNs. In this letter, we propose a novel single-image super-resolution (SISR) algorithm named Wider Channel Attention Network (WCAN) for remote sensing images. Firstly, the channel attention mechanism is used to adaptively recalibrate the importance of each channel at the middle of the wider attention block (WAB). Secondly, we propose the Local Memory Connection (LMC) to enhance the information flow. Finally, the features within each WAB are fused to take advantage of the network’s representation capability and further improve information and gradient flow. Analytic experiments on a public remote sensing data set (UC Merced) show that our WCAN achieves better accuracy and visual improvements against most state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Image fusion

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