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Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios

China Communications 2020年第2期17卷 138-148页

作者： Shilian Zheng Shichuan Chen Peihan Qi Huaji Zhou Xiaoniu Yang Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of ChinaXidian UniversityXi’an 710071China

Spectrum sensing is a key technology for cognitive *** present spectrum sensing as a classification problem and propose a sensing method based on deep learning *** normalize the received signal power to overcome the effects of noise power *** train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new *** also use transfer learning strategies to improve the performance for real-world *** experiments are conducted to evaluate the performance of this *** simulation results show that the proposed method performs better than two traditional spectrum sensing methods,i.e.,maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based *** addition,the experimental results of the new untrained signal types show that our method can adapt to the detection of these new ***,the real-world signal detection experiment results show that the detection performance can be further improved by transfer ***,experiments under colored noise show that our proposed method has superior detection performance under colored noise,while the traditional methods have a significant performance degradation,which further validate the superiority of our method.

关键词： spectrum sensing deep learning convolutional neural network cognitive radio spectrum management

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A constructive approach to minimal realization problem of 2D systems

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控制理论与应用（英文版） 2009年第3期7卷 335-343页

作者： Huijin FAN Hua CHENG Li XU The Key Laboratory of Image Processing and Intelligent control and Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei 430074 China Faculty of Systems Science and Technology Akita Prefectural University Akita 015-0055 Japan

Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the minimal Roesser model realization problem for a class of 2D systems which does not belong to the clarified categories. As one of the main results, a constructive realization procedure is first proposed. Based on the proposed procedure, sufficient conditions and explicit construction for minimal realizations of the considered 2D systems are shown. In addition, possible variations and applications of the obtained results are discussed and illustrative examples are presented.

关键词： 2D systems Minimal realization Roesser local state-space model

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基于第二代Bandelet域隐马尔可夫树模型的图像分割

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自动化学报 2009年第5期35卷 498-504页

作者：侯彪徐婧刘凤焦李成 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

第二代Bandelet可以充分利用图像的内在几何正则性特点,并能自适应获得图像的最优表示.本文采用隐马尔可夫树(Hidden Markov tree,HMT)模型对图像的第二代Bandelet系数建模,通过多尺度参数训练和基于上下文的最大后验概率进行图像分割.... 详细信息

第二代Bandelet可以充分利用图像的内在几何正则性特点,并能自适应获得图像的最优表示.本文采用隐马尔可夫树(Hidden Markov tree,HMT)模型对图像的第二代Bandelet系数建模,通过多尺度参数训练和基于上下文的最大后验概率进行图像分割.为了评价本文方法的性能,我们分别选择合成纹理图像、航拍图像和SAR图像进行实验,并与小波域HMT模型分割方法(WD-HMTseg)和Contourlet域HMT模型分割方法(CHM Tseg)进行比较说明算法的有效性.实验结果表明本文方法不但在边缘准确性和区域一致性上有明显改进,而且也降低了纹理图的错分概率.

关键词：图像分割第二代Bandelet 隐马尔可夫树模型小波 Contourlet变换

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Directional Filter for SAR images Based on Nonsubsampled Contourlet Transform and Immune Clonal Selection

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International Journal of Automation and computing 2009年第3期6卷 245-253页

作者： Xiao-Hui Yang Li-Cheng Jiao Deng-Feng Li Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi＇an 710071 PRC Institute of Applied Mathematics School of Mathematics and Information Sciences Henan University Kaifeng 475004 PRC

A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.

关键词： Directional filter nonsubsampled contourlet transform （NSCT） immune clonal selection optimization （ICSO） syntheticaperture radar （SAR）.

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Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Sun, Y.U.-Qiu Tian, Jin-Wen Liu, Jian School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept. of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)078039092X

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image will be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical. © 2005 IEEE.

关键词： Pattern recognition

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Remaining Useful Life Prediction for a Multi-stack Solid Oxide Fuel Cell System with Degradation Interactions

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1207-1214页

作者： Xiaojuan Wu Liangfei Xu Yang Huang Danan Yang Junhao Wang Houjun Wang Xi Li School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 610054China State Key Lab of Automotive Safety and Energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China School of Artificial Intelligencei and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and TechnologyWuhan 430074China

Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel *** from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of *** response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is ***,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.

关键词： Degradation interaction multi-stack remaining useful life(RUL) solid oxide fuel cell(SOFC)

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Computer simulation for medical ultrasound c-mode imaging based on 2d array

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2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012

作者： Hua, Shaoyan Yuchi, Ming Ding, Mingyue Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Biomedical Engineering Department School of life Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783037854389

C-mode imaging is one of the ultrasound imaging modalities. Compared with other modalities, e.g. A-mode, B-mode, M-mode, and Doppler, C-mode is mainly developed and used in industry testing. The potential of C-mode imaging for medical application has not been fully explored. In this paper, we design one 2-d plane array transducer through using the point spread function (PSF), and apply the 2d array transducer for C-mode imaging. The simulation results show that the generated C-mode images can display the anatomic structure and the pathological changes on the biological tissue. © (2012) Trans Tech Publications, Switzerland.

关键词： Optical transfer function

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Facial Expression Recognition In-the-Wild with Deep Pre-trained Models 17th

Facial Expression Recognition In-the-Wild with Deep Pre-tra...

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17th European Conference on Computer Vision, ECCV 2022

作者： Li, Siyang Xu, Yifan Wu, Huanyu Wu, Dongrui Yin, Yingjie Cao, Jiajiong Ding, Jingting Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Ant Group Hangzhou China

ISBN: (纸本)9783031250743

Facial expression recognition (FER) is challenging, when transiting from the laboratory to in-the-wild situations. In this paper, we present a general framework for the Learning from Synthetic Data Challenge in the 4th Affective Behavior Analysis In-The-Wild (ABAW4) competition, to learn as much knowledge as possible from synthetic faces with expressions. To cope with four problems in training robust deep FER models, including uncertain labels, class imbalance, mismatch between pretraining and downstream tasks, and incapability of a single model structure, our framework consists of four respective modules, which can be utilized for FER in-the-wild. Experimental results on the official validation set from the competition demonstrated that our proposed approach outperformed the baseline by a large margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Face recognition

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Approximate Jacobian control of robot manipulators without joint velocity measurements

Approximate Jacobian control of robot manipulators without j...

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IEEE International Conference on Cyber Technology in Automation,control,and intelligent Systems

作者： Liang, Xinwu Huang, Xinhan Wang, Min Key Laboratory of Image Processing and Intelligent Control Dept. of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781612849102

So far, all of the approximate Jacobian controllers for robot manipulators proposed in the literatures have assumed that the exact joint velocity measurements are available. In this paper, we propose alternative controller designs without the use of joint velocity measurements. To provide the joint velocities used by the controllers, we introduce the well-known sliding mode observers to estimate the robot manipulator states. In addition, Lyapunov analysis is presented to show that the combined controller-observer designs can achieve asymptotical stability in the sliding patch. Simulation results are also presented to show the performance of the proposed methods. © 2011 IEEE.

关键词： Velocity measurement

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A double-integrator system for distributed optimization of convex cost functions 29

A double-integrator system for distributed optimization of c...

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第29届中国控制与决策会议

作者： Ngoc-Tu Tran Xuan Feng Wen-Yuan Xu Na Zhan Xi Wang School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Electric Power Company

ISBN: (纸本)9781509046584

In this paper,the distributed optimization problem is investigated under a second-order multi-agent *** the proposed algorithm,each agent solves the optimization via local computation and information exchange with its neighbors through the communication ***,in comparison with the existing second-order distributed optimization algorithms,the proposed algorithm is much simpler due to one coupled information exchange among the agents is *** achieve the optimization,the distributed algorithm is proposed based on the consensus method and the gradient *** optimal solution of the problem is thus obtained with the design of Lyapunov function and the help of LaSallel's Invariance Principle.A numerical simulation example and comparison of proposed algorithm with existing works are presented to illustrate the effectiveness of the theoretical result.

关键词： Second-order multi-agent systems Distributed optimization Consensus Lyapunov function Gradient algorithm

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