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IEEE Transactions on Radar Systems 2024年 2卷 1076-1088页

作者： Sun, Jun Yuan, Ye Sabrina Greco, Maria Gini, Fulvio University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China University of Pisa Information Engi-neering Pisa56126 Italy

The rapid development of cooperative techniques and anti-jamming methods in modern radar systems has significantly improved the mission performance and survivability of radars. In practical applications, the single jammer system cannot cope with the cooperative technology of the radar system due to its single interference pattern and spatial angle. To combat distributed radar systems, in this article, we construct and solve a resource management problem with the goal of minimizing the false target rejection probability, while being constrained by the deception jamming power budget of the multijammer system. First, the posterior Cramér-Rao lower bounds (PCRLBs) including target state and deception parameters related to the radar system under deception jamming are derived. On this basis, a false target discriminator is designed and the corresponding rejection probability is derived, which is regarded as the metric to assess the deception jamming performance. Then, the deception jamming power scheduling (DJPS) problem of the multijammer system for cooperatively combating distributed radar systems is constructed, subject to the system resource configurations. Due to the nonconvexity of the false target rejection probability, the formulated problem is inherently nonconvex. To effectively address this problem, a modified particle swarm optimization (MPSO) algorithm is presented. Numerical simulations verify that the proposed strategy and MPSO algorithm show superior deception jamming performance in combating distributed radar systems. © 2023 IEEE.

关键词： Cramer-Rao bounds

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A Scalable and Generalized Deep Ensemble Model for Road Anomaly Detection in Surveillance Videos

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Computers, Materials & Continua 2024年第12期81卷 3707-3729页

作者： Sarfaraz Natha Fareed A.Jokhio Mehwish Laghari Mohammad Siraj Saif A.Alsaif Usman Ashraf Asghar Ali Department of Information Technology Quaid-e-Awam University of EngineeringScience&TechnologyNawabshah67480Pakistan Department of Software Engineering Sir Syed University of Engineering and TechnologyKarachi75000Pakistan Electrical Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia School of Business Torrens UniversitySydneyNSW 2007Australia School of Engineering and Information Technology The University of New SouthWales(UNSD)CanberraACT 2604Australia

Surveillance cameras have been widely used for monitoring in both private and public sectors as a security *** Circuits Television(CCTV)Cameras are used to surveillance and monitor the normal and anomalous ***-world anomaly detection is a significant challenge due to its complex and diverse *** is difficult to manually analyze because vast amounts of video data have been generated through surveillance systems,and the need for automated techniques has been raised to enhance detection *** paper proposes a novel deep-stacked ensemble model integrated with a data augmentation approach called Stack Ensemble Road Anomaly Detection(SERAD).SERAD is used to detect and classify the four most happening road anomalies,such as accidents,car fires,fighting,and snatching,through road surveillance videos with high *** SERAD adapted three pre-trained Convolutional Neural Networks(CNNs)models,namely VGG19,ResNet50 and *** stacking technique is employed to incorporate these three models,resulting in much-improved accuracy for classifying road abnormalities compared to individual ***,it presented a custom real-world Road Anomaly Dataset(RAD)comprising a comprehensive collection of road images and *** experimental results demonstrate the strength and reliability of the proposed SERAD model,achieving an impressive classification accuracy of 98.7%.The results indicate that the proposed SERAD model outperforms than the individual CNN base models.

关键词： Convolutional neural network transfer learning stack ensemble learning road anomaly detection data augmentation

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N:ZnO/MoS_(2)-heterostructured flexible synaptic devices enabling optoelectronic co-modulation for robust artificial visual systems

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Nano Research 2024年第3期17卷 1902-1912页

作者： Lei Xu Wenxiao Wang Yang Li Yonghui Lin Wenjing Yue Kai Qian Qinglei Guo Jeonghyun Kim Guozhen Shen School of Information Science and Engineering University of JinanJinan 250022China School of Microelectronics Shandong UniversityJinan 250101China Department of Electronic Convergence Engineering Kwangwoon UniversitySeoul 01897Republic of Korea School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China

With the merits of non-contact,highly efficient,and parallel computing,optoelectronic synaptic devices combining sensing and memory in a single unit are promising for constructing neuromorphic computing and artificial visual *** on this,a N:ZnO/MoS_(2)-heterostructured flexible optoelectronic synaptic device is developed in this work,and its capability in mimicking the synaptic behaviors is systemically investigated under the electrical and light *** synaptic functions,including synaptic plasticity,long-term/short-term memory,and learning-forgetting-relearning property,have been achieved in this synaptic ***,an artificial visual memory system integrating sense and memory is emulated with the device array,and the visual memory behavior can be regulated by varying the light ***,the optoelectronic co-modulation behavior is verified by applying mixed electric and light signals to the *** detail,a transient recovery property is discovered when the electric signals are applied in synergy during the decay of the light response,of which property facilitates the development of robust artificial visual ***,by superimposing electrical signals during the light response process,a differentiated response of the array is achieved,which can be used as a proof of concept for the color perception of the artificial visual system.

关键词： flexible synaptic device synaptic plasticity optoelectronic synapse robust visual memory optoelectronic co-modulation artificial visual system

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Simulation on the Membrane Potential Variations by THz Unipolar Stimulation with Triangle Envelope

Simulation on the Membrane Potential Variations by THz Unipo...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Bo, Wenfei Che, Rong Guo, Lemeng Zhang, Xiaobo Liu, Qiang Tao, Bo Duan, Baosong Li, Yuansheng Gong, Yubin National University of Defense Technology College of Information and Communication China University of Electronic Science and Technology of China School of Electronic Science and Engineering China

ISBN: (纸本)9798350375909

Terahertz has recently shown new application prospects in non-invasive brain-machine communications. Terahertz stimulation can induce the information communication of cells. Cell membrane potentials are significant electrical variable in cell communication. However, the membrane potential variations are far from being understood fully under the terahertz stimulation. This paper studies the membrane potential variations of a cell under terahertz unipolar stimulation with triangle envelope, by means of the cell model of ion flow considering Na+, K+-ATPase and hydrophilic pores in cell membrane. From the numerical results, except where the cell membrane in the cell is nearly parallel to the terahertz electric fields, the absolute values of the membrane potentials increase first and then decrease towards zero under the stimulation. During those variation processes, the membrane potentials vibrate at the terahertz frequency the same as the stimulation. Besides, the variation rates of the membrane potentials show quasi pulse train forms at the same terahertz frequency during the stimulation, and the envelopes of the variation rates show triangle envelope, and additionally the triangle envelopes of the variation rates at some polar angles of the cell are out of shape near the end of the terahertz unipolar stimulation. This indicates that the triangle envelope of the terahertz unipolar stimulation can be delivered into the membrane potentials of the biological cell, and shows a potential way of transferring the triangle envelope signal in terahertz unipolar picosecond pulse train into biological cells for the applications in the brain-machine communications. © 2024 IEEE.

关键词： Cell membranes

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DP-GenFL: a local differentially private federated learning system through generative data

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science China(information sciences) 2023年第8期66卷 275-276页

作者： Jun LI Kang WEI Chuan MA Feng SHU School of Electronic and Optical Engineering Nanjing University of Science and Technology Zhejiang Lab Key Laboratory of Computer Network and Information Integration (Southeast University) Ministry of Education School of Information and Communication Engineering Hainan University

With the rapid development of the Internet of Things(Io T),the amount of data from intelligent devices is propagating at unprecedented scales. Meanwhile, machine learning(ML),which relies heavily on such data, is revolutionizing many aspects of our lives [1]. However, conventional centralized ML offers little scalability for efficiently processing this huge amount of data.

关键词： Learning systems

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Deep Learning-based Recognizing Liquids Using a Multi-resonance Microwave Sensor

Deep Learning-based Recognizing Liquids Using a Multi-resona...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Zhou, Yifan Yong, Jinglei Peng, Jinyang Li, Peng Tong, Meisong Zhang, Yunjing Soochow University School of Electronic and Information Engineering China Tongji University Department of Electronic Science and Technology China

ISBN: (纸本)9798350375909

In this paper, a microwave sensor is investigated by etching multiple different split ring resonators (SRRs) on the ground layer, thus obtaining multiple complementary split ring resonators (CSRRs). In order to improve the sensitivity, we control the size of the CSRRs between λ/4 to λ/2, so that the the stored energy is large near the resonances. The model uses a two-port microstrip line coupled with the CSRRs to extract the insertion loss (S21) in the range of 5-8 GHz, rather than the usual analysis just near a single resonant points. In addition, we find that the size of the CSRRs and the distance between the CSRRs and microstrip line have great influences on its resonant frequency and Q-factor of the sensor. We detect unknown liquids in two cases. First, different types of liquids including water, ethanol, ether, and methanol are investigated, and we find that the characteristics of S21 are distinctive. Secondly, a challenge task that detecting different concentrations of ethanol solutions is carried out. In this case, the changes in their permittivity are small, indicating small changes in the characteristics of S21. Considering the fact that most of liquid containers on the market have grooves, hollow bottom, and different thickness of walls, the measured S21 of liquids is inconsistent, let alone the placement position error between bottles and the sensing area in rapid test. To solve the problem, we use a feedforward neural network (FNN) by the backpropagation method to process the measured S21 in a wide band. The results show that the accuracy of detecting different liquids by the deep learning method is 100% and of detecting the same liquid with different concentrations is 99%. Compared with the traditional method, the proposed one is insusceptible to random errors. The nondestructive liquid detection proposed in this work has good future in detecting suspicious liquids in the market. © 2024 IEEE.

关键词： Microwave sensors

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Hyperbolic map unravels eight regions in temperature volatility regionalization of China' Mainland

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Chinese Physics B 2024年第12期33卷 526-534页

作者： Yuxuan Song Changgui Gu Muhua Zheng Aixia Feng Yufei Xi Haiying Wang Huijie Yang School of Management University of Shanghai for Science and TechnologyShanghai 200093China School of Physics and Electronic Engineering Jiangsu UniversityZhenjiangJiangsu 212013China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

Abrupt temperature volatility has detrimental effects on daily activities,macroeconomic growth,and human *** abrupt temperature volatility and thus diminishing its negative impacts can be achieved by exploring homogeneous regions of temperature volatility and analyzing the driving *** investigate the regionalization of temperature volatility in China's mainland,a network constructed by the cosine similarity of temperature volatility series from China's mainland was embedded in hyperbolic ***,we partitioned the network on the hyperbolic map using the critical gap method and then found eight regions in ***,a network of communities was constructed while the interaction among communities was *** yields a perspective of temperature volatility regionalization that can accurately reflect factors including altitude,climate type,and the geographic location of *** analysis demonstrates that the regionalization in the hyperbolic map is distinct from provinces and has a realistic basis:communities in southwest China show strong correlations due to the temperature sensitivity to altitude,and communities in northern China show a convergence in the area of Dingxi,Gansu,mainly owing to the strong temperature sensitivity to climate *** a consequence,node distributions and community divisions in the hyperbolic map can offer new insights into the regionalization of temperature volatility in China's *** results demonstrate the potential of hyperbolic embedding of complex networks in forecasting future node associations in real-world data.

关键词： complex network hyperbolic embedding community detection regionalization

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Research on Purely Azimuth Passive Localization Model for UAV Formation Flight

Research on Purely Azimuth Passive Localization Model for UA...

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2024 International Conference on Frontiers of electronic, Electrical and Computer science, ICFEECS 2024

作者： Tang, Chenchong Ying, Beining Gu, Ruoxuan Yang, Shengying School of Information and Electronic Engineering Zhejiang University of Science and Technology HangZhou China School of Science Zhejiang University of Science and Technology HangZhou China

The practical applications of unmanned aerial vehicle (UAV) formation passive localization demand high accuracy and anti-interference ability. In this paper, a novel passive localization model based on analytical geometry and improved damped Gauss-Newton optimization method is proposed, which incorporates the improved damped Gauss-Newton algorithm and the error-based iterative algorithm for real-time coordinate correction of formation. Through Matlab simulation experiments, the proposed error-based iterative algorithm can stabilize the flight formation after only 24 iterations, and the distance error between each UAV and the specified position is only 1.2%. Moreover, in the case of signal loss, only four UAVs are required to transmit signals to localize a circular flying formation consisting of 10 UAVs. The model provides a theoretical method for passive localization and control of UAV formations in purely azimuthal flights. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： MATLAB

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Multiband Radar Signal Fusion Based on Double Threshold Sparsity Adaptive Matching Pursuit

Multiband Radar Signal Fusion Based on Double Threshold Spar...

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2023 International Applied Computational Electromagnetics Society Symposium, ACES-China 2023

作者： Qin, Xinxin Zhang, Ying Zhao, Huapeng School of Information and Communication Engineering University of Electronic Science and Technology China School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781733509657

This paper presents a novel multiband fusion method named double threshold sparsity adaptive matching pursuit (DTSAMP) to improve the range resolution of radar. In particularly, the adaptive threshold and step size is designed to improve the precision of parameter estimation and resist the effects of noise. Based on sparse reconstruction (SR) theory and the geometry theory of diffraction (GTD) model, sparse subbands complete incoherent compensation, and then coherent subbands are utilized to obtain a full-band signal by DTSAMP. Also, the proposed method does not require prior information on the number of scattering centers. Simulations verify the effectiveness of proposed method. © 2023 Applied Computational Electromagnetics Society (ACES).

关键词： Computation theory

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Robust Detector Designing for FDA-MIMO Radar With Training Data in Gaussian Noise

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IEEE Transactions on Aerospace and electronic Systems 2025年第3期61卷 7787-7802页

作者： Gui, Limin Huang, Bang Wang, Wen-Qin division Thuwal23955 Saudi Arabia University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Huzhou313001 China

This paper presents the design of robust detectors for frequency diverse array multiple-input multiple-output (FDA-MIMO) radar in the presence of Gaussian noise with an unknown covariance matrix. It aims to address the challenge of detecting the target of a coherent return from an appointed cell under test. Our primary focus is on the case of signal mismatch, specifically considering the two-dimensional mismatch, including the target and the Doppler steering vectors. To tackle these issues, we introduce a fictitious signal with a specified structure in addition to the nominal steering vector, thereby forming a new hypothesis testing model. By making use of this model, we further derive robust detectors utilizing the generalized likelihood ratio test (GLRT) and Wald test in the presence of training data. Besides, a parametric detector is implemented, which includes robust GLRT as a particular case. The proposed detectors own constant false alarm rate (CFAR) properties under the null hypothesis. The effectiveness of designed algorithms is verified by comparing their performance with those of their given counterparts. Moreover, numerical examples illustrate that the functionality of presented detectors is better compared to GLRT, adaptive matched filter (AMF), Wald, and multiple-input multiple-output-Wald (MIMO-Wald) detectors in terms of robustness against signal mismatches. © 1965-2011 IEEE.

关键词： Covariance matrix

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