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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Song, Xiaorui Wu, Lingda Hao, Hongxing Graduate School Space Engineering University Beijing China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9781538642108

The hyperspectral image(HSI) generated by most imaging spectrometer systems is constantly disturbed by noise. In this research, we introduced an HSI denoising method based on the theory of sparse coding extended to the spectral domain. The algorithm employs variable separation method and augmented Lagrangian method in sparse coding and constitutes the adaptive dictionary from the pixel spectral vectors extracted from the noisy image. Our results demonstrate that the HSI denoising performance is related to the sparsity of the representation. The effectiveness of the new adaptive sparse coding based approach to hyperspectral denoising, termed HyDeASp, is illustrated in a series of experiments on synthetic and real-world data where it outperforms the state-of-the-art. © 2018 IEEE.

关键词： Image denoising

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Growth modes of quasicrystals involving intermediate phases and a multistep behavior studied by phase field crystal model

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Physical Review Materials 2020年第2期4卷 023403-023403页

作者： Zhencheng Jiang Silong Quan Ning Xu Linghui He Yong Ni CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei 230026 People's Republic of China School of Mechanical and Electronic Engineering East China University of Technology Nanchang 330013 People's Republic of China Hefei National Laboratory for Physical Sciences at the Microscale CAS Key Laboratory of Microscale Magnetic Resonance and Department of Physics University of Science and Technology of China Hefei 230026 People's Republic of China CAS Center for Excellence in Complex System Mechanics

Understanding the microscopic kinetics of quasicrystal formation via nucleation and growth is crucial. Here, we report unusual pathways to nucleation and growth of dodecagonal quasicrystals via a phase field crystal model incorporating a two-length-scale potential. Under certain thermodynamic parameters, both quasicrystal growths via heterogeneous and homogeneous nucleation may be associated with a multistep behavior and the transient appearance of triangular and intermediate phases, different from classical nucleation pathways. The metastable intermediate phase spontaneously occurs to bridge the triangular phase and quasicrystal nuclei of different orientations to reduce the total free energy of the system. Decomposition of an undercooled fluid phase into quasicrystal phase shows a multistep pathway wherein the triangular phase and the intermediate phase may occur faster than the quasicrystal phase, when the growth rate of one length-scale ordering is significantly different from the other and the subsequent competing and coupling of both length scales are involved. The calculated structure factor, radial distribution function, and the aperiodic tiling structure of the intermediate phase explain why it appears during the quasicrystal formation.

关键词： Growth processes Phase transitions Quasicrystals Phase-field modeling

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Modified ddpg algorithm applied to simulation supervised learning 48

Modified ddpg algorithm applied to simulation supervised lea...

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48th International Conference on Computers and Industrial Engineering, CIE 2018

作者： Jia, Zhengxuan Xiao, Yingying Zhao, Zhilong Lin, Tingyu State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

With rapid development of machine learning, supervised learning and reinforcement learning have witnessed a considerable success. However, some problems like the absence of supervising signal in supervised learning are not yet solved. In this paper, a novel approach has been proposed based on the deep deterministic policy gradient algorithm to address such kind of problems, forming the training of an agent supervised by the simulation environment. As verification, our proposed approach is applied to a modified tower defense game, and the experimental results confirmed the effectiveness of our proposed approach. © 2018, Curran Associates Inc. All rights reserved.

关键词： Supervised learning

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Fusion of panchromatic and multispectral images via morphological operator and improved PCNN in mixed multiscale domain 10

Fusion of panchromatic and multispectral images via morpholo...

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10th IAPR Workshop on Pattern Recognition in Remote Sensing, PRRS 2018

作者： Jiao, Jiao Lingda, Wu Department of Graduate Management Space Engineering University Beijing China Simulation Laboratory Space Engineering University Science and Technology on Complex Electronic System Beijing China

ISBN: (纸本)9781538684795

In order to effectively combine the spectral information of the multispectral (MS) image with the spatial details of the panchromatic (PAN) image and improve the fusion quality, a fusion method based on morphological operator and improved pulse coupled neural network (PCNN) in mixed multi-scale (MM) domain is proposed. Firstly, the MS and PAN images are decomposed by nonsubsampled shearlet transform (NSST) to low- and high-frequency coefficients, respectively;secondly, morphological filter-based intensity modulation (MFIM) technology and stationary wavelet transform (SWT) are applied to the fusion of the low-frequency coefficients;an improved PCNN model is employed to the fusion of the high-frequency coefficients;thirdly, the final coefficients are reconstructed with inverse NSST. The experimental results on QuickBird satellite demonstrate that the proposed method is superior to five other kinds of traditional and popular methods: HIS, PCA, SWT, NSCT-PCNN and NSST-PCNN. The proposed method can improve the spatial resolution effectively while maintaining the spectral information well. The experimental results show that the proposed method outperforms the other methods in visual effect and objective evaluations. © 2018 IEEE.

关键词： Image fusion

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complex Value Image Group Sparse Coding Denoising Algorithm Based on K-means Clustering Method

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Ruan Jian Xue Bao/Journal of Software 2019年 30卷 17-24页

作者： Liu, Bo-Yu Wu, Ling-Da Hao, Hong-Xing Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

Sparse coding has been widely used in complex value image demising. In recent years, the proposed block sparse coding has more advantages in noise filtering and noise reduction because it can make full use of the similarity of patches in the same block. In this paper, a K-means clustering method based sparse demising algorithm for complex image grouping is studied. By improving the clustering algorithm, the grouping effectiveness of K-means algorithm for sparse block coding algorithm is verified. The online complex dictionary training algorithm is used to acquire the coded dictionary quickly, and the sparse coding of block image is realized by using the grouping orthogonal matching pursuit algorithm. By inducing the similarity of the coding in each block, the coding of noise in the block is effectively suppressed and the noise reduction of the complex value image is improved. In order to verify the effectiveness of the proposed algorithm, the demising of simulated and real interferometric synthetic aperture radar images is quantitatively analyzed, which proves that the proposed algorithm has a certain improvement in peak signal-to-noise ratio (PSNR) compared with the previous block sparse coding algorithm. Finally, the real interferometric synthetic aperture radar image is demised, which further verifies the de-noising ability of the proposed algorithm for real noise. © Copyright 2019, Institute of Software, the Chinese Academy of sciences. All rights reserved.

关键词： Image denoising

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Transient Fault Diagnosis Algorithm based on Feature Classification and Its Application in High-Power Laser facility

Transient Fault Diagnosis Algorithm based on Feature Classif...

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Chinese Control and Decision Conference, CCDC

作者： Qiang Ren Hang Gao Hailei Ren Baoran An Tianyou Yun Xiaoli Wang Institute of Computer Application China Academy of Engineering Physics Mianyang State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha Institute of Fluid Physics China Academy of Engineering Physis MianYang China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

High-power laser facility plays an import role both in scientific research and military application, and the occurred faults are usually transient. In this paper, a transient fault diagnosis algorithm based on feature classification is proposed, and the algorithm has been applied in the high-power laser facility. The method extracts the features of input data with an autoencoder network. And based on the extracted features, a multi-layer full connection neural network is adopted for fault diagnosis. By comparing the results with those obtained by traditional fault diagnosis methods, the performance of the algorithm has been verified.

关键词： Feature extraction Fault diagnosis Circuit faults Neural networks Principal component analysis Kernel Transient analysis

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Design of High-Gain Cavity-Backed Planar Spiral Antenna Based on Arc-Shaped Metasurface

Design of High-Gain Cavity-Backed Planar Spiral Antenna Base...

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Jian-yi Chu Lin Peng Jing Ma Bin Shi Yan-ru Hua Zhi-peng Li Xing Jiang Si-min Li Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin Guangxi China Science and Technology on special system simulation laboratory Beijing Simulation Center Beijing China

A high-gain cavity-backed planar spiral antenna based on arc-shaped metasurface (ASM) is proposed and designed. The unidirectional beam of the Archimedean planar spiral antenna (ASA) is achieved by loading the λ/4-distance metal reflector back cavity. A metasurface consisted of arc-shaped unit cells is located at 28mm above the spiral. The simulated results indicate that the impedance bandwidth of the proposed antenna is 4.53-8.29GHz and the axial ratio bandwidth of 3dB is 5.33-8.29GHz. The gain of the cavity-backed planar spiral antenna is increased by dBi in the frequency band 4.5-6.25GHz due to the proposed ASM, and the proposed antenna presents a peak gain of 12.67 dBi at 5.5GHz.

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Design of Dynamically Tunable Broadband Polarization Converter in Terahertz Frequency Based on Graphene Strips

Design of Dynamically Tunable Broadband Polarization Convert...

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Tian-Cheng Zheng Lin Peng Xiao Liu Jing Ma Bin Shi Zhi-Hua Zhao Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin Guangxi China Science and Technology on special system simulation laboratory Beijing Simulation Center Beijing China

A dynamically tunable polarization converter has been proposed in this paper, which has a multi-layer structure consisting of an orthogonal cross metallic, graphene strips, spacer substrate and a gold back ground layer. In this paper, the proposed polarization converter can transform the linear polarization incident waves into its cross polarization in reflection mode in terahertz (THz) frequency within an ultra-wideband, and the polarization conversion ratio (PCR) of the proposed structure has over 97% from 4.1 THz to 7.1 THz. Furthermore, by adjusting the chemical potential (or Fermi energy) of the graphene strips, the operating frequency band can be changed dynamically.

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Broadband Polarization-Conversion Metasurface for a Cassegrain Antenna with High Polarization Purity

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Physical Review Applied 2019年第1期12卷 014009-014009页

作者： Wen-Long Guo Guang-Ming Wang Ke Chen Hai-Peng Li Ya-Qiang Zhuang He-Xiu Xu Yijun Feng Air and Missile Defense College Air Force Engineering University Xi’an 710051 China Department of Electronic Engineering School of Electronic Science and Engineering Nanjing University Nanjing 210093 China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing 100076 China

Polarization conversion has been widely explored in the study of metasurfaces in order to achieve broad operation bandwidths, but its application is still restricted to a few practical scenarios. We design a broadband cross-polarization conversion metasurface and apply it to form a directionally radiated Cassegrain antenna with a low profile and high polarization purity. A quasi-I-shaped meta-atom is first optimized with both high cross-polarization conversion efficiency and a full span of phase modulation in a broad bandwidth. With a hyperbolic phase profile imposed on the surface, a metasurface is engineered that can conduct both focusing and polarization conversion into its cross-polarization component. Then, by introducing a polarized grating as a subreflector and simultaneously fixing the designed metasurface as the main reflector, a planar Cassegrain antenna is facilitated with a low profile, high gain, and high polarization purity in a broad frequency band. This strategy of broad-band polarization conversion and its attempt to design a Cassegrain antenna lays a foundation for high-performance functional devices, promising great potential in real-world applications.

关键词： Metamaterials Polarization of light Radio frequency techniques Devices Wireless communication networks Electromagnetic wave theory Microwave techniques

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Affinity Propagation for Hyperspectral Band Selection 2

Affinity Propagation for Hyperspectral Band Selection

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2018 2nd International Symposium on Resource Exploration and Environmental science, REES 2018

作者： Ren, Zhiwei Wu, Lingda Department of Graduate Management Space Engineering University Beijing101416 China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

Because hyperspectral images have the characteristics of high correlation between bands and strong information redundancy, the reduction in dimension of hyperspectral images is an important step in the pre-processing of hyperspectral images. Band selection can preserve the physical meaning of the original data while reducing dimension and has application in many aspects. Affinity Propagation Clustering (AP) is a clustering method proposed by Fray et al. in 2007. AP clusters based on the correlation between data points and treats all data points as potential cluster centers. This paper proposes a band selection method based on AP clustering, which introduces wavelet transform into the calculation of similarity and preference value in clustering algorithm. The dimensionality reduction results are input into the minimum distance classifier for classification, and the classification accuracy was calculated. The dataset is validated by the Indiana Pines dataset. The experimental results verify the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Wavelet transforms

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