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Independent dual beams generated by array element division in integrated optical phased arrays

Chinese Optics Letters 2024年第7期22卷 35-41页

作者： Guihan Wu Yu Xin Lemeng Leng Xiang Ji Shichong Yang Kaifei Tang Quan Luo Hongsheng Luo Jinshan Su Wei Jiang College of Engineering and Applied Sciences Nanjing UniversityNanjing 210023China National Laboratory of Solid-State Microstructures Nanjing 210093China Key Laboratory of Intelligent Optical Sensing and Manipulation Ministry of EducationNanjing UniversityNanjing 210023China Jiangsu Key Laboratory of Artificial Functional Materials Nanjing UniversityNanjing 210023China Key Laboratory of Vibration Signal Capture and Intelligent Processing Yili Normal UniversityIli 835000China

Optical phased arrays(OPAs)have broad application prospects due to their advanced capability in beamforming and *** this work,we achieve independent dual beams in the far field by dividing the array elements of the OPA,with the maximum scanning range reaching 100°.Based on the working principle of OPAs,theoretical considerations of such multibeam generation are presented.A phase data allocation approach for OPAs in the presence of fabrication-induced random phase variation is *** of large ensembles of OPAs with various levels of random residual phase errors have been conducted to help analyze the *** approach can help OPAs realize multi-beams for light detection and ranging(LiDAR).

关键词： optical phased arrays beamforming phase error calibration array element division

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A Spectrum Based Algorithm for Image Classification

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Chinese Journal of Electronics 2023年第3期18卷 427-430页

作者： Nian Wang Jiang Zhang Jun Tang Yizheng Fan Dong Liang Key Laboratory of Intelligent Computing and Signal Processing Anhui University Education Ministry Hefei China Hefei Teachers College Hefei China Department of Mathematics Anhui University Hefei China

In this paper, a novel algorithm for image classification is presented which uses the projective value of adjacency spectrum as classified samples. Firstly, the eigenvalues of adjacency matrices constructed on the feature point-sets of images are obtained by singular value decomposition. Secondly, the eigenvalues are projected onto the eigenspace by means of the covariance matrix. Finally, image classification is performed by adopting RBF and PNN neural networks as classifiers respectively. Mean-while, some theoretical analyses are given to support the proposed method.

关键词： Neural networks education Eigenvalues and eigenfunctions Classification algorithms Matrix decomposition Covariance matrices Image classification

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Dual-Control Reconfigurable intelligent Metasurface: Design and Realization

Dual-Control Reconfigurable Intelligent Metasurface: Design ...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Kangtai Zheng Kwok L. Chung Yuzhong Li Guoming Lai Jianhai Wang Yingsong Li School of Computer Science and Engineering Huizhou University Huizhou China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

A dual-control reconfigurable intelligent metasurface (DC-RIMS) composed of $24\times 22$ symmetric cells in the 5G mid-band is proposed. The DC-RIMS of non-artificial-magnetic-conductor type provides a smaller phase resolution of $60^{\mathrm{o}}$ with 2 bits under normal incidence. Angular sensitivities of the RIMS under oblique incidence are investigated. Our results show that the reflection responses at elevation angles are more sensitive than the azimuth angles, whereas the maximum phase differences are differed from each polarization. The horizontal one increases to $220^{\mathrm{o}}$ whereas the vertical one reduces to $150^\mathrm{o}$ as compared with overlapped $180^{\mathrm{o}}$ under normal incidence.

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Machine learning prediction of network dynamics with privacy protection

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Physical Review Research 2022年第4期4卷 043076-043076页

作者： Xin Xia Yansen Su Linyuan Lü Xingyi Zhang Ying-Cheng Lai Hai-Feng Zhang The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei 230601 China

Predicting network dynamics based on data, a problem with broad applications, has been studied extensively in the past, but most existing approaches assume that the complete set of historical data from the whole network is available. This requirement presents a great challenge in applications, especially for large, distributed networks in the real world, where data collection is accomplished by many clients in a parallel fashion. Often, each client only has the time series data from a partial set of nodes, and the client has access to only partial time stamps of the whole set of time series data and the partial structure of the network. Due to privacy concerns or license-related issues, the data collected by different clients cannot be shared. Accurately predicting the network dynamics while protecting the privacy of different parties is a critical problem in modern times. Here, we propose a solution based on federated graph neural networks (FGNNs) that enables the training of a global dynamic model for all parties without data sharing. We validate the working of our FGNN framework through two types of simulations to predict a variety of network dynamics (four discrete and three continuous dynamics). As a significant real-world application, we demonstrate successful prediction of state-wise influenza spreading in the USA. Our FGNN scheme represents a general framework to predict diverse network dynamics through collaborative fusing of the data from different parties without disclosing their privacy.

关键词： Collective behavior in networks

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A Through-hole Antenna Array for Joint Optical and Millimeter Sensing Applications

A Through-hole Antenna Array for Joint Optical and Millimete...

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International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： Sixian Qian Lulu Meng Zhixiang Huang Yingsong Li Tian Hong Loh Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Electromagnetic & Electrochemical Technologies Department National Physical Laboratory Middlesex United Kingdom

A novel millimeter wave sensing antenna array is proposed for application in miniature detection and sensing devices suitable for operating in multiple scenarios, e.g., collecting in the face of video and infrared, and other device materials in complex electromagnetic environments to achieve delightful sensing results. The proposed antenna array is designed to work at 30 GHz which is considered to integrate the optical devices and millimeter radar together by using a number of holes in the millimeter antenna array. Two different excitation modes are considered in the constructed design, where many holes are installed in the millimeter array, which aims to integrate the optical imaging cameras. In this design, the presented array serves as a radar to detect and get sensing results. Since the optical components are not metal and have a little effect on the performance of the antenna array, we use the holes to model the optical cameras to investigate the performance of the radiation patterns and impedance bandwidth.

关键词： Millimeter wave devices Laser radar Radar imaging Radar antennas Optical imaging Cameras Optical sensors

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Cross-Modality Perturbation Synergy Attack for Person Re-identification 38

Cross-Modality Perturbation Synergy Attack for Person Re-ide...

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38th Conference on Neural Information processing Systems, NeurIPS 2024

作者： Gong, Yunpeng Zhong, Zhun Qu, Yansong Luo, Zhiming Ji, Rongrong Jiang, Min School of Informatics Xiamen University China School of Computer Science and Information Engineering Hefei University of Technology China The Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Key Laboratory of Digital Protection and Intelligent Processing of Intangible CulturalHeritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University Fujian Xiamen361005 China

In recent years, there has been significant research focusing on addressing security concerns in single-modal person re-identification (ReID) systems that are based on RGB images. However, the safety of cross-modality scenarios, which are more commonly encountered in practical applications involving images captured by infrared cameras, has not received adequate attention. The main challenge in cross-modality ReID lies in effectively dealing with visual differences between different modalities. For instance, infrared images are typically grayscale, unlike visible images that contain color information. Existing attack methods have primarily focused on the characteristics of the visible image modality, overlooking the features of other modalities and the variations in data distribution among different modalities. This oversight can potentially undermine the effectiveness of these methods in image retrieval across diverse modalities. This study represents the first exploration into the security of cross-modality ReID models and proposes a universal perturbation attack specifically designed for cross-modality ReID. This attack optimizes perturbations by leveraging gradients from diverse modality data, thereby disrupting the discriminator and reinforcing the differences between modalities. We conducted experiments on three widely used cross-modality datasets, namely RegDB, SYSU, and LLCM. The results not only demonstrate the effectiveness of our method but also provide insights for future improvements in the robustness of cross-modality ReID systems. © 2024 Neural information processing systems foundation. All rights reserved.

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Excellent Student Training in Shielding Effectiveness Analysis with International Cooperation 10

Excellent Student Training in Shielding Effectiveness Analys...

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10th IEEE International Conference on Computer Science and Network Technology, ICCSNT 2022

作者： Li, Yingsong Huang, Zhixiang Wang, Meiyu Jiang, Tao Sinkevich, Eugene Mordachev, Vladimir College of Information and Communication Engineering Harbin Engineering University Harbin15001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China Belarusian State University of Informatics and Radioelectronics Emc RandD Laboratory Minsk Belarus

ISBN: (数字)9781665470612

ISBN: (纸本)9781665470612

We present the excellent student training scheme in shielding effectiveness analysis with international cooperation of Belarus. As we know, the shielding is vital for modern information devices due to the radiating around us. Herein, the shielding effectiveness is important for training excellent students to master the design of the frequency selective components. In this method, we teach the students to use the EM simulation tools to construct different EM structures for obtaining the shielding, and the performance of these structures are verified from the simulations and measurements. Using this shielding effectiveness training scheme, a frequency selective surface is presented, simulated and discussed to analyze its performance. In future, the excellent student training methods given herein for shielding effectiveness can be expanded to develop other EM structures. © 2022 IEEE.

关键词： International cooperation

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Pctlfusion: A Progressive Fusion Network Via Contextual Texture Learning for Infrared and Visible Image

SSRN

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SSRN 2024年

作者： Lu, Yixiang Gong, Daiwei Zhao, Dawei Maksim, Davydau Gao, Qingwei The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electrical Engineering and Automation Anhui University Hefei230601 China Belarusian State University of Informatics and Radioelectronics Minsk Belarus

The objective of infrared and visible image fusion is to generate a fused image that contains rich texture details and salient targets. However, most of the existing fusion methods tend to focus on preserving texture details in visible image and salient targets in infrared image, ignoring the fact that infrared image have richer texture details and better visual effects than visible image under low-light conditions. In other words, differences in information sources under the condition of illumination imbalance is ignored in setting the task goal. In addition, existing network designs usually ignore multimodal information interactions during the coding phase, which may result in loss of information. In this work, we propose a progressive fusion network via contextual texture learning for infrared and visible image, termed as PCTLFusion. To enhance the limited texture information, we design a content and contextual texture learning module (CCTLM) to model the texture and content of both the source images, respectively. Then, an affine transform-based multimodal pre-fusion module (ATMPM) is designed to learn and pre-fuse the complementary and similar enhanced information, which achieves information interaction during encoding. To learn fully feature information using multilayers, we iterate CCTLM and ATMPM three times in the process of model forming. Finally, the fused image is reconstructed by decoding the output of the last ATMPM. Numerous experiments show that our proposed fusion algorithm is superior to the state-of-the-art existing methods in both subjective and objective evaluations. © 2024, The Authors. All rights reserved.

关键词： Textures

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A Circularly Polarized Antenna with a Loading Metal Strip for GPS L1 band

A Circularly Polarized Antenna with a Loading Metal Strip fo...

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International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： Lulu Meng Sixian Qian Zhixiang Huang Yingsong Li Tian Hong Loh Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Electromagnetic & Eletrochemical Technologies Department National Physical Laboratory Middlesex United Kingdom

The paper presents a novel circular polarization(CP) antenna loading with a parasitic ring metal strip, which is designed for global positioning system (GPS) L1 band applications. The antenna consists of a defected ground plane with four arc-slots and a circular slot, a dielectric substrate, a parasitic ring metal strip, and a radiating patch (RP) with a arc-slot. By rotating the parasitic ring metal strip to opening slot on the RP, the antenna can be transformed from left-handed circular polarization (LHCP) to right-handed circular polarization (RHCP). The size of the antenna can be reduced by using slots on the ground. The simulation and optimization results show that impedance bandwidth of the L/RHCP antenna is over 100 MHz, and the axial ratio bandwidth is over 20 MHz.

关键词： Polarization Slot antennas Loading Metals Bandwidth Loaded antennas Optimization

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Efficient Finite-Difference Time-Domain Method for Solving Electromagnetic Scattering in Layered Anisotropies

Efficient Finite-Difference Time-Domain Method for Solving E...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Yilin Kang Yuxian Zhang Xiaoli Feng Lixia Yang Zhixiang Huang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education and with the Information Materials and Intelligent Sensing Laboratory of Anhui Province Industry-Education-Research Institute of Advanced Materials and Technology for Integrated Circuits and with School of Electronic and Information Engineering Anhui University Hefei China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

In this article, we propose an efficient numerical method for layered models based on the conventional finite difference time-domain (FDTD) method. The three-dimensional (3-D) layered model is compressed into one-dimensional (1-D) calculation, which improves the problem of large space memory and long running time for 3-D modeling while ensuring the accuracy and feasibility of the algorithm. On the one hand, by employing the transformation relationship between the transverse wave vector and the field in space, the expanded Maxwell's rotation equations are simplified, so that the equation system only retains the spatial transformation in the propagation direction. This processing allows for the calculation of the propagation characteristics of layered media without requiring more computational resources. On the other hand, to ensure the universality of the algorithm, a fully tensor anisotropic medium is selected for detecting the propagation data. At the same time, we design the layered structure and conduct the consistent 3-D modeling in the simulation software COMSOL. The results showed that our proposed efficient numerical algorithm greatly reduced the loss of computing resources while ensuring accuracy.

关键词： Solid modeling Three-dimensional displays Accuracy Tensors Software algorithms Vectors Mathematical models Numerical models Time-domain analysis Finite difference methods

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