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13th International Conference on Control, Automation and information sciences, ICCAIS 2024

作者： Wang, Cong Zhang, Guoxin Liang, Yunfei Yue, Gao Yi, Wei School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331542047

In this paper, the problem of joint target detection and localization in Dual-Function Radar-Communication (DFRC) systems is studied. A communication-assisted sensing mechanism is designed to fully utilize spectrum resources and enhance the joint detection and localization capabilities of DFRC systems. At the core, we construct two objective functions for joint detection and localization, applicable to scenarios where the communication signal is either known or unknown. In particular, for the scenario where the communication signal is unknown, the constructed objective function becomes a high-dimensional non-convex optimization problem, making direct solution computationally expensive. To address this, we further develop an efficient Expectation-Maximization-based General-ized Likelihood Ratio Test (EM-GLRT) detector to solve the problem. Numerical simulations validate the effectiveness of the proposed method, demonstrating that it can efficiently achieve communication-assisted joint detection and localization tasks in DFRC systems. © 2024 IEEE.

关键词： Convex optimization

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LKAW: A Robust Watermarking Method Based on Large Kernel Convolution and Adaptive Weight Assignment

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Computers, Materials & Continua 2023年第4期75卷 1-17页

作者： Xiaorui Zhang Rui Jiang Wei Sun Aiguo Song Xindong Wei Ruohan Meng Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China School of Instrument Science and Engineering Southeast UniversityNanjing211189China School of Teacher Education Nanjing University of Information Science&TechnologyNanjing210044China School of Computer Science Engineering Nanyang Technological UniversitySingapore

Robust watermarking requires finding invariant features under multiple attacks to ensure correct *** learning has extremely powerful in extracting features,and watermarking algorithms based on deep learning have attracted widespread *** existing methods use 3×3 small kernel convolution to extract image features and embed the ***,the effective perception fields for small kernel convolution are extremely confined,so the pixels that each watermarking can affect are restricted,thus limiting the performance of the *** address these problems,we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss *** uses large-kernel depth-wise convolution to extract features for learning large-scale image information and subsequently projects the watermarking into a highdimensional space by 1×1 convolution to achieve adaptability in the channel ***,the modification of the embedded watermarking on the cover image is extended to more *** the magnitude and convergence rates of each loss function are different,an adaptive loss weight assignment strategy is proposed to make theweights participate in the network training together and adjust theweight ***,a high-frequency wavelet loss is proposed,by which the watermarking is restricted to only the low-frequency wavelet sub-bands,thereby enhancing the robustness of watermarking against image *** experimental results show that the peak signal-to-noise ratio(PSNR)of the encoded image reaches 40.12,the structural similarity(SSIM)reaches 0.9721,and the watermarking has good robustness against various types of noise.

关键词： Robust watermarking large kernel convolution adaptive loss weights high-frequency wavelet loss deep learning

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Naive Bayesian Classifier-based Collaborative Tracking and Recognition for Multi-radar Systems

Naive Bayesian Classifier-based Collaborative Tracking and R...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Ma, Shuoyang Yuan, Ye Yi, Wei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350375909

This paper presents a naive Bayesian recognition and classification method based on extended Kalman filter, designed for multi-target tracking scenarios using multiple radars. The approach employs covariance intersection (CI) fusion to integrate data from diverse sources and obtains the target state, accordingly. A naive Bayesian classifier is trained with various features extracted from the target state, enhancing the classification process. The numerical findings reveal the algorithm's robust performance in scenarios with multi-dimensional feature inputs, demonstrating its efficacy in classifying diverse target types. © 2024 IEEE.

关键词： Extended Kalman filters

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Compact Wideband Balun and Balun Bandpass Filter Based on Broadside Coupled Three-Line Structures

Compact Wideband Balun and Balun Bandpass Filter Based on Br...

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2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024

作者： Qi, Han-Rui Wang, Xuedao School of Electronic and Information Engineering Jinling Institute of Technology Nanjing China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350383317

An ultra-wideband balun prototye and a wideband balun bandpass filter (BPF) with compact sizes are proposed based on the coupled three-line structure. Firstly, the ultra-wideband balun is constructed by a partially coupled three-line where the terminal of central half-wavelength (λg/2) input line is grouded and two λg/2 sidelines are open-circuited with two output feeding ports oppositely placed. By improving the coupling strength with broadside coupling implemented by two-layer stacked subatrates, ultra-wideband performance can be achieved. Then, by loading two λg/4 short-ended stub resonators at both open terminals of the λg/2 sidelines, high selective filtering response with two transmission zeros around the passband is obtained. Then, according to the design equations derived from equivalent circuit, two prototypes of the proposed balun and balun BPF are designed in theory and simulated. Final results show that the wideband balun BPF is centered at 1.7 GHz with a 3-dB fractional bandwidth of 85.8% and a compact size of 0.35λg × 0.23λg. Within the passband, the phase difference is within 180°±2° and the amplitude imbalance is less than 0.2 dB. © 2024 IEEE.

关键词： Bandpass filters

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Human Gait Recognition Algorithm Based on MobileNetV1 with Attention Mechanism 3

Human Gait Recognition Algorithm Based on MobileNetV1 with A...

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3rd International Conference on Artificial Intelligence and Computer engineering, ICAICE 2022

作者： Zhang, Jinsha Zhang, Xuedong School of Computer and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China

ISBN: (纸本)9781510663473

For embedded modern equipment, the current gait recognition algorithm model is difficult to deploy on it due to a large amount of gait frame image data, slow network processing speed, complex structure and low computational efficiency. In this paper, a lightweight convolutional network model integrating the attention mechanism is proposed. The algorithm first performs morphological processing on the image, extracts the gait contour image, and calculates the gait energy image;Integrates the attention mechanism with MobileNetV1;The feature information of the image is effectively extracted, and the parameters of the network are reduced. A number of body method validation experiments are conducted in the CAISIAB gait database of the Chinese Academy of sciences, and the experimental results are significantly improved with other deep learning models. © 2023 SPIE.

关键词： Computational efficiency

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Novel optical soliton molecules formed in a fiber laser with near-zero net cavity dispersion

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Light(science & Applications) 2023年第2期12卷 272-283页

作者： Xiao Hu Jun Guo Jun Wang Jie Ma Luming Zhao Seongwoo Yoo Dingyuan Tang Julong College Shenzhen Technology University518118 ShenzhenChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore jiangsu Key Laboratory of Laser Materials and Devices School of Physics and Electronic EngineeringJiangsu Normal UniversityXuzhouChina School of Optical and Electronic Information Huazhong University of Science and Technology430074 WuhanChina

Soliton molecules(SMs)are stable bound states between *** in fiber lasers are intensively investigated and embody analogies with matter *** experimental studies on SMs formed by bright solitons,including soliton-pair,soliton-triplet or even soliton-quartet molecules,are ***,study on soliton-binding states between bright and dark solitons is *** this work,the formation of such novel SMs in a fber laser with near-zero group velocity dispersion(ZGVD)is ***,these SMs are formed because of the incoherent cross-phase modulation of light and constitute a new form of SMs that are conceptually analog to the multi-atom molecules in *** research results could assist the understanding of the dynamics of large SM *** findings may also motivate potential applications in large-capacity transmission and all-optical information storage.

关键词： fiber optical laser

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Strengthened Dominance Relation NSGA-Ⅲ Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

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Computers, Materials & Continua 2024年第1期78卷 375-392页

作者： Liang Zeng Junyang Shi Yanyan Li Shanshan Wang Weigang Li School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan430068China School of Information Science and Engineering Wuhan University of Science and TechnologyWuhan430081China

The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing *** involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple *** Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling ***,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and *** enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence ***,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex *** validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test *** experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.

关键词： Multi-objective job shop scheduling non-dominated sorting genetic algorithm differential evolution simulated binary crossover

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Multifunctional light-field modulation based on hybrid nonlinear metasurfaces

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Chinese Physics B 2023年第10期32卷 73-89页

作者：钱树航王凯杨加兴关超龙华陆培祥 Wuhan National Laboratory for Optoelectronics and School of Physics Huazhong University of Science and TechnologyWuhan 430074China School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China

The generation characteristics of nonlinear optical signals and their multi-dimensional modulation at micro-nano scale have become a prominent research area in nanophotonics,and also the key to developing various novel nonlinear photonics *** recent years,the demand for higher nonlinear conversion efficiency and device integration has led to the rapid progress of hybrid nonlinear metasurfaces composed of nanostructures and nonlinear *** a joint platform of stable wavefront modulation,nonlinear metasurface and efficient frequency conversion,hybrid nonlinear metasurfaces offer a splendid opportunity for developing the next-generation of multipurpose flat-optics *** article provides a comprehensive review of recent advances in hybrid nonlinear metasurfaces for light-field *** advantages of hybrid systems are discussed from the perspectives of multifunctional light-field modulation,valleytronic modulation,and quantum ***,the remaining challenges of hybrid metasurfaces are summarized and future developments are also prospected.

关键词： light-field modulation hybrid metasurfaces nonlinear optics two-dimensional materials

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Toward Robust DDOS Detection in SDN: Leveraging Feature engineering and Ensemble Learning 21

Toward Robust DDOS Detection in SDN: Leveraging Feature Engi...

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21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Madoune, Sid Ali Senouci, Sarra Setitra, Mohamed Ali Dingde, Jiang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Mechanical and Electronic Engineering University of Electronic Science and Technology of China Chengdu611731 China University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798331519254

This paper introduces a novel approach for detecting Distributed Denial of Service (DDoS) attacks in software-Defined Networking (SDN) environments, addressing the critical need for accurate and efficient threat detection in modern network infrastructures. The proposed method integrates dimensionality reduction, feature engineering, and machine learning (ML) into a cohesive pipeline. Specifically, it combines Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) for dimensionality reduction, followed by K-Means clustering to enhance feature representation. Cluster assignments (Benign/Attack) derived from the t-SNE-reduced data are incorporated as a new feature, enabling classifiers to detect latent attack patterns more effectively than traditional methods. When evaluated on a real-world SDN dataset, the method significantly outperformed existing approaches, achieving over 99.9% accuracy with Random Forest (RF) and XGBoost classifiers. Notably, XGBoost processed data in just 0.2 seconds, demonstrating exceptional suitability for real-time applications. Furthermore, the ensemble model, combining RF and XGBoost, achieved the highest overall accuracy of 99.93%, an AUC of 1.00, and an execution time of 1.61 seconds. These results underscore the proposed approach's substantial improvements in accuracy and computational efficiency making it a robust solution for addressing critical network security challenges in SDN environments. © 2024 IEEE.

关键词： Dimensionality reduction

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AI-Assisted Project-Based Learning and Exploration in the Field of electronic information engineering Majors 18th

AI-Assisted Project-Based Learning and Exploration in the...

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18th International Conference on Computer science and Education, ICCSE 2023

作者： Yu, Li Wu, Ming-Wei Cen, Gang Xi, Yong-Xin Yan, Xin Qiu, Tian-Hao School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789819707904

Artificial intelligence (AI) is advancing rapidly and finding its way into various industries. Universities are placing a high priority on incorporating AI into professional education. However, for students who are not majoring in AI, applying AI technology to projects can be challenging. To foster the development of application-oriented talents in the AI era, this article presents an illustrative example of project-based learning that focuses on the use of AI tools for assisted education in the context of blind navigation vehicles. The project specifically concentrates on core AI applications, such as pedestrian detection using Raspberry Pi and line tracking for blind navigation. Voice broadcasting is employed to facilitate interaction with visually impaired individuals. The project is carried out in teams, with an emphasis on utilizing user-friendly AI tools for project-based education and practical experimentation. By integrating theory and practice, students have the opportunity to enhance their practical skills, deepen their understanding of AI, strengthen teamwork, improve communication skills, and foster innovative thinking. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Artificial intelligence

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