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LF-CNN:Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification

computer Modeling in engineering & sciences 2022年第4期131卷 429-444页

作者： Chengfan Li Lan Liu Junjuan Zhao Xuefeng Liu School of Computer Engineering and Science Shanghai UniversityShanghai200444China Key Laboratory for Digital Land and Resources of Jiangxi Province East China University of TechnologyNanchang330013China School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghai201620China School of Communication&Information Engineering Shanghai UniversityShanghai200444China

Target detection of small samples with a complex background is always difficult in the classification of remote sensing *** propose a new small sample target detection method combining local features and a convolutional neural network(LF-CNN)with the aim of detecting small numbers of unevenly distributed ground object targets in remote sensing *** k-nearest neighbor method is used to construct the local neighborhood of each point and the local neighborhoods of the features are extracted one by one from the convolution *** the local features are aggregated by maximum pooling to obtain global feature *** classification probability of each category is then calculated and classified using the scaled expected linear units function and the full connection *** experimental results show that the proposed LF-CNN method has a high accuracy of target detection and classification for hyperspectral imager remote sensing data under the condition of small *** drawbacks in both time and complexity,the proposed LF-CNN method can more effectively integrate the local features of ground object samples and improve the accuracy of target identification and detection in small samples of remote sensing images than traditional target detection methods.

关键词： Small samples local features convolutional neural network(CNN) k-nearest neighbor(KNN) target detection

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Multimedia Classification via Tensor Linear Discriminant Analysis

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IEEE Transactions on Broadcasting 2024年第4期70卷 1139-1152页

作者： Chang, Shih-Yu Wu, Hsiao-Chun Yan, Kun Chih-Hao Huang, Scott Wu, Yiyan San Jose State University Department Of Applied Data Science San JoseCA95192 United States Louisiana State University School Of Electrical Engineering And Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center For Ai Applications Taoyuan32003 Taiwan Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Department Of Information And Telecommunication Guilin541004 China National Tsing Hua University Department Of Electrical Engineering Hsinchu300 Taiwan Western University Department Of Electrical And Computer Engineering LondonONN6A 3K7 Canada

Linear discriminant analysis (LDA) is a well-known feature-extraction technique for data analytic and pattern classification. As the dimensionality of multimedia data has increased in this big era, it is often to characterize data by tensors. Over the past two decades, researchers have thus explored to extend LDA to the general tensor space, especially in two common ways: LDA of tensors using tensor decomposition methods (by conversion of tensors to matrices) and LDA of tensors built upon the T-product. However, both of the aforementioned approaches have restrictions thereby. A critical problem about how to carry out LDA of arbitrary scatter tensors based on the Einstein product still remains unsolved by the existing methods. Therefore, we propose a novel tensor LDA (a.k.a. TLDA) approach, which can carry out the LDA of arbitrary-dimensional scatter-tensors without any need of tensor decomposition. Besides, for reducing the computation time, we also design a parallel paradigm to execute our proposed TLDA in this work. Numerical experiments conducted over real multimedia data demonstrate the efficacy of our proposed new TLDA in terms of classification accuracy. Moreover, the comparison of the classification accuracies, computational-complexities, and memory-complexities of our proposed novel TLDA scheme and other existing tensor-based LDA methods is made. By leveraging TLDA for high-dimensional feature extraction, segmentation, and user-item interaction data processing, future multimedia recommendation systems can facilitate more accurate, engaging, and satisfactory user experience over the Internet. © 1963-12012 IEEE.

关键词： Tensors

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Tutorial on laser-based visible light communications[Invited]

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Chinese Optics Letters 2024年第9期22卷 126-136页

作者： Yuqi Hou Yue Wang Zengxin Li Meixin Liu Shulan Yi Xiaoqian Wang Liang Xia Guangyi Liu Jianyang Shi Ziwei Li Junwen Zhang Nan Chi Tien Khee Ng Boon S.Ooi Chao Shen Key Laboratory for Information Science of Electromagnetic Waves Ministry of EducationSchool of Information Science and TechnologyFudan UniversityShanghai 200433China ZGC Institute of Ubiquitous-X Innovation and Applications Beijing 100876China Photonics Laboratory Electrical and Computer EngineeringDivision of ComputerElectrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia China Mobile Research Institute Beijing 100876China

Facing escalating demands for high-speed,large-bandwidth,and low-latency wireless data links,laser communication technology has emerged as a promising *** free-space optical communication conventionally utilizes nearinfrared light sources,there has been growing interest in exploring new spectral resources,including visible ***,laser-based white light has been demonstrated in visible light communication(VLC),with a unique capability to seamlessly integrate with illumination and display *** review summarizes the key devices and system technologies in semiconductor-laser-based white light for VLC-related *** recent advances and many emerging applications in the evolution of lighting,display,and communication are discussed.

关键词： visible light communication LiFi laser lighting GaN laser semiconductor laser

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System Modelling, Numerical Simulations and Experimental Validation of High Capacity FSO Data Transmission in DWDM Communication Employing Optical Frequency Comb 24

System Modelling, Numerical Simulations and Experimental Val...

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24th IEEE International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2024

作者： Rajaram, Narmada Avazpour, Mahrokh Barry, Liam Hinzer, Karin Hall, Trevor Atieh, Ahmad School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada School of Electronic Engineering Dublin City University Radio and Optics Communications Laboratory GlasnevinDublin 9 Ireland University of Ottawa Optiwave System Inc 7 Capella Court Ottawa Canada

ISBN: (纸本)9798350390537

Dense Wavelength Division Multiplexing (DWDM) optical technology allows transmission of many wavelengths in a single optical channel. In this paper, system modelling and numerical simulations are demonstrated for high-capacity data transmission using an Optical Frequency Comb (OFC). An OFC is generated using fiber loop modulation technique and simulations are carried out using commercially available simulation software -OptiSystem. An OFC with excellent flatness is obtained, which is essential for noise and error reduction. Each comb line is modulated with data and the DWDM multiplexed signal is transmitted over a free-space optical (FSO) channel. The system performance is assessed in terms of Bit Error Rate (BER) and range of the FSO channel. Our experimental results demonstrate that our system aligns well with simulation and can generate an OFC confirming the potential of our approach for applications such as optical communication networks. © 2024 IEEE.

关键词： Bit error rate

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Directional emission of a readout resonator for qubit measurement

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Physical Review Applied 2024年第3期22卷 034035页

作者： Alec Yen Yufeng Ye Kaidong Peng Jennifer Wang Gregory Cunningham Michael Gingras Bethany M. Niedzielski Hannah Stickler Kyle Serniak Mollie E. Schwartz Kevin P. O’Brien Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Harvard John A. Paulson School of Engineering and Applied Sciences Lexington Massachusetts 02421 USA

We propose and demonstrate transmission-based dispersive readout of a superconducting qubit using an all-pass resonator, which preferentially emits readout photons toward the output. This is in contrast to typical readout schemes, which intentionally mismatch the feedline at one end so that the readout signal preferentially decays toward the output. We show that this intentional mismatch creates scaling challenges, including larger spread of effective resonator linewidths due to nonideal impedance environments and added infrastructure for impedance matching. A future architecture using multiplexed all-pass readout resonators would avoid the need for intentional mismatch and potentially improve the scaling prospects of quantum computers. As a proof-of-concept demonstration of “all-pass readout,” we design and fabricate an all-pass readout resonator that demonstrates insertion loss below 1.17 dB at the readout frequency and a maximum insertion loss of 1.53 dB across its full bandwidth for the lowest three states of a transmon qubit. We demonstrate qubit readout with an average single-shot fidelity of 98.1% in 600 ns; to assess the effect of larger dispersive shift, we implement a shelving protocol and achieve a fidelity of 99.0% in 300 ns.

关键词： Circuit quantum electrodynamics Optoelectronics Quantum error correction Quantum information with solid state qubits Quantum measurements Superconducting quantum optics Superconducting devices Microwave techniques

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Entropic and Operational Characterizations of Dynamic Quantum Resources

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IEEE Transactions on Information Theory 2025年

作者： Ji, Kaiyuan Chitambar, Eric Cornell University School of Electrical and Computer Engineering IthacaNY14850 United States University of Illinois at Urbana-Champaign Coordinated Science Laboratory Department of Electrical and Computer Engineering UrbanaIL61801 United States

We offer new methods for characterizing general closed and convex quantum resource theories, including dynamic ones, based on entropic concepts and operational tasks. We propose a resource-theoretic generalization of the quantum conditional min-entropy, termed the free conditional min-entropy (FCME), in the sense that it quantifies an observer's "subjective"degree of uncertainty about a quantum system given that the observer's information processing is limited to free operations of the resource theory. Using this generalized concept, we provide a complete set of entropic conditions for free convertibility between quantum states or channels in any closed and convex quantum resource theory. We also derive an information-theoretic interpretation for the resource global robustness of a state or a channel in terms of a mutual-information-like quantity based on the FCME. Apart from this entropic approach, we characterize dynamic resources by also analyzing their performance in operational tasks. We construct operationally meaningful and complete sets of resource monotones with these tasks, which enable faithful tests of free convertibility between quantum channels. Finally, we show that every well-defined robustness-based measure of a channel can be interpreted as an operational advantage of the channel over free channels in a communication task. © 1963-2012 IEEE.

关键词： Quantum channel

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Large-scale coherent Ising machine based on optoelectronic parametric oscillator

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Light(science & Applications) 2022年第12期11卷 2972-2981页

作者： Qizhuang Cen Hao Ding Tengfei Hao Shanhong Guan Zhiqiang Qin Jiaming Lyu Wei Li Ninghua Zhu Kun Xu Yitang Dai Ming Li State Key Laboratory on Integrated Optoelectronics Institute of SemiconductorsChinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijingChina School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghaiChina Peng Cheng Laboratory ShenzhenChina

Ising machines based on analog systems have the potential to accelerate the solution of ubiquitous combinatorial optimization *** some artificial spins to support large-scale Ising machines have been reported,e.g.,superconducting qubits in quantum annealers and short optical pulses in coherent Ising machines,the spin stability is fragile due to the ultra-low equivalent temperature or optical phase *** this paper,we propose to use short microwave pulses generated from an optoelectronic parametric oscillator as the spins to implement a large-scale Ising machine with high *** proposed machine supports 25,600 spins and can operate continuously and stably for ***,the proposed Ising machine is highly compatible with high-speed electronic devices for programmability,paving a low-cost,accurate,and easy-to-implement way toward solving real-world optimization problems.

关键词： stability oscillator coherent

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Surrogate-Assisted Multi-Class Collaborative Teaching and Learning Optimizer for High-Dimensional Industrial Optimization Problems

Surrogate-Assisted Multi-Class Collaborative Teaching and Le...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Wang, Ziqi Yuan, Haitao Yang, Jinhong Zhang, Jia College of Computer Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Cssc Systems Engineering Research Institute Beijing China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9781665410205

Swarm intelligence and evolutionary algorithms are widely applied in industrial scheduling, mobile edge computing, etc due to their strong robustness and fast optimization speed. However, some real-world industrial optimization problems involve numerous decision variables, known as high-dimensional problems. Current algorithms often require considerable computational resources to evaluate objective function values because of high-dimensional decision spaces. Moreover, they are also prone to be trapped in local optima. To solve the above problems, this work proposes an improved algorithm named Surrogate-assisted Multi-class Collaborative Teaching and learning optimizer (SMCT). A multi-class collaborative teaching and learning optimizer is proposed as a base optimizer to improve exploration and exploitation abilities. Furthermore, an autoencoder-assisted radial basis function is proposed as the surrogate model to replace true function evaluations, thereby saving computational resources and balancing the complexity and accuracy in fitting true models. Finally, experimental results demonstrate that SMCT surpasses its existing peers in both search accuracy and convergence speed across eight high-dimensional benchmark functions. © 2024 IEEE.

关键词： Scheduling algorithms

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Time-Sensitive Local Differential Privacy-Based Federated Learning for Vehicular Digital Twin Networks 1st

Time-Sensitive Local Differential Privacy-Based Federated Le...

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1st International Symposium on Intelligent Computing and Networking, ISICN 2024

作者： Sun, Kangkang Xu, Hansong Zhang, Xiaojin Hua, Kun Li, Jianhua Shanghai Key Laboratory of Integrated Administration Technologies for Information Security School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Electrical Engineering California Polytechnic State University San Luis ObispoCA93407 United States

ISBN: (纸本)9783031674464

The Vehicular Digital Twin Network (VDTN) integrates digital twin (DT) models of connected and autonomous vehicles (CAVs) to facilitate smart sensing, management, and collaboration in the physical realm. VDTN synchronizes extensive data on roads, vehicles, and operators, including sensitive information like user location and driving habits. To address these privacy concerns and enhance model efficiency, we introduce a time-sensitive local differential privacy-based federated learning framework (FedTS) tailored for VDTN. This framework assigns varying privacy levels to DT models during model-sharing intervals, considering the time sensitivity of VDTNs. Comparative analysis with state-of-the-art algorithms, such as differentially-private stochastic gradient descent (DP-SGD), demonstrates significant improvements in both security and model performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Federated learning

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Defective Microstrip Structure Based Phase Shifter with Reduced Size for Phased Antenna Array Applications 12

Defective Microstrip Structure Based Phase Shifter with Redu...

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12th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Khan, Hajra Khan, Shahid Nasir, Jamal Ali Shah, Syed Ahson Dalarsson, Mariana Alibakhshikenari, Mohammad Comsats University Islamabad Department of Electrical and Computer Engineering Pakistan Hanyang University Applied Bioelectronics Laboratory Seoul Korea Republic of School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Stockholm Sweden Universidad Carlos Iii de Madrid Department of Signal Theory and Communications Spain

ISBN: (纸本)9798350358056

In this work, we propose a small-size and low-cost phase shifter based on defective microstrip structure (DMS) technique, with a modified reconfigurable unit cell (MRDMS) for WLAN applications at 5.2 GHz. The phase shifter is made up of an MRDMS unit, created by etching slots on a simple microstrip line with an outline of three bridges. To further increase the phase shift, a T-shaped slot is introduced in the central bridge and PIN diodes on the edges of the outer bridges are used. By switching the diodes on and off, the MRDMS unit cell is capable of operating in a variety of different modes to give a phase shift of 37.71° at 5.2 GHz. Additionally, MRDMS unit cells are cascaded for higher phase shift as required. Cascaded two- and four-cell phase shifters were designed and simulated in HFSS and a parametric study on various parameters was conducted to show the detailed operating properties of the proposed phase shifter. Compared to previously reported research, the present study shows that two cascaded phase shifters introduce 75.08° phase shifts and 151.75°, respectively. To the best of our knowledge, this is the maximum phase shift obtained by a phase shifter based on MRDMS. © 2023 IEEE.

关键词： defected microstrip structure phase shifter reconfigurable microwave system

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