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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Research on lightweight detection algorithm of Infrared Image based on YOLOv5 4

Research on lightweight detection algorithm of Infrared Imag...

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4th International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2024

作者： Zhang, Wenyi Mo, Hongwei Wu, Songling Li, Xiaomin Harbin Engineering University School of Intelligent Science and Engineering Harbin150000 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

At present, infrared image can show good detection effect in complex environment because of its unique imaging characteristics, which brings a lot of convenience to people's production and life. However, because the infrared image contains a great lot of unnecessary information, it has great requirements for computing power and memory capacity, so it is challenging to satisfy the demands of real-time detection on resource-constrained portable mobile devices. To solve this problem, this paper proposes a refined lightweight algorithm built upon the YOLOv5, which changes the backbone network of the model to GhostNet network, introduces CA attention mechanism into the model to improve the detection effect of small targets, and changes the loss function of the model to Focal-EIoU loss function to improve the location effect of the boundary box and quicken the model's rate of convergence. Then replace the conventional convolution used in the sampling process of the model with the space-to-depth convolution module, in order to enhance the model's detection performance on low-resolution images and enable the extraction of more feature information. According to the experimental results, the enhanced detection algorithm is just 1% less than the initial YOLOv5 algorithm, and the model volume and floating point calculation are reduced by 31.9% and 36% respectively. This is better suited for deployments that are lightweight. © 2024 SPIE.

关键词： Convolution

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Scattering Characteristics-guided Self-supervised Learning for Target Classification in SAR Images 24

Scattering Characteristics-guided Self-supervised Learning f...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Zhong, Honghu Li, Jianhao Shi, Hao Fang, Zhonghao Chen, Liang Institute of Radar Technology Beijing Institute of Technology Beijing China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing China Innovation Center of Beijing Institute of Technology Chongqing Chongqing401120 China

ISBN: (纸本)9798400716720

With the advancement of science and technology, the spatial resolution of spaceborne Synthetic Aperture Radar (SAR) images has achieved sub-meter precision, enabling the classification and identification of targets. Notably, the rapid and accurate classification of aircraft targets using SAR images has become a significant application requirement. Nevertheless, challenges persist in the classification of targets within aircraft remote sensing images. This paper introduces a novel method aimed at enhancing the scattering characteristics in SAR images to address issues associated with discrete imaging pixels, strong scattering characteristics, and the consequent difficulty in distinguishing aircraft features. The proposed method systematically correlates the discrete SAR image scattering characteristics, thereby facilitating the extraction of characteristic information pertaining to the edge contours of aircraft targets. Recognizing the limitations of traditional supervised classification methods, which often demand substantial manually labeled information, this study integrates self-supervised contrastive learning to mitigate labeling costs. Additionally, acknowledging the imbalanced distribution of samples across different categories and the prevalent "long tail"effect, a weighted loss function is introduced to rectify the imbalance and enhance the network's focus on the learning of underrepresented samples. The efficacy of the proposed method is evaluated using a self-established dataset. The results demonstrate a 1.48% increase in accuracy compared to the original self-supervised method, indicating an improvement in the classification performance for categories characterized by an imbalanced sample distribution. © 2024 ACM.

关键词： Image classification

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者： Yuan Ge Jie Li Wenwu Jiang Lidan Wang Shukai Duan School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified national Institute of Standards and technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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Research Progress and Prospect of High-Speed Vehicle control technology Based on Reinforcement Learning

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Advances in Astronautics 2025年 1-9页

作者： Lu, Kunfeng Wang, Weili Liu, Xiaodong Huang, Wanwei Jia, Chenhui Yu, Yue Beijing Aerospace Automatic Control Institute Beijing China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China

High reliability and intelligence mark the cutting-edge development trend of high-speed vehicle control technology. This research focuses on the progress of high-speed vehicle control technology based on reinforcement learning, and sorts out its application in control parameter tuning, compensation control, and end-to-end control. Focusing on the development framework of intelligent control safety and efficiency, this paper deeply analyzes the challenges of safety, training efficiency, and interpretability faced by high-speed vehicle in reinforcement learning control, and proposes feasible paths and development directions for future research.

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Bioprofiling and vaccine development for Zika virus

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science China Life sciences 2025年

作者： Huiping Shi Shengyong feng Abid Naeem Baoying Huang Wenjie Tan Lulu Zheng Xingjie Liang Minghui Yang Yuanyu Huang School of Life Science Advanced Research Institute of Multidisciplinary Science Aerospace Center Hospital School of Medical Technology Key Laboratory of Molecular Medicine and Biotherapy Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering Beijing Institute of Technology School of Basic Medical Sciences Tsinghua University National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases Key Laboratory of Biosafety National Health Commissions National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology of China Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology (BIT)

Zika virus(ZIKV) has emerged as a global health priority due to its association with severe congenital abnormalities, including microcephaly and neonatal mortality in infants born to infected mothers. In adults, ZIKV infection is epidemiologically linked to Guillain-Barré Syndrome(GBS). These clinical manifestations prompted the World Health Organization(WHO) to declare ZIKV a Public Health Emergency of International Concern(PHEIC). The antibody-dependent enhancement(ADE) phenomenon further complicates vaccine development and therapeutic strategies. While substantial progress has been made in elucidating ZIKV biology through multidisciplinary approaches, no vaccines or therapies have been clinically approved. This review examines ZIKV-associated risks by analyzing transmission dynamics, viral architecture, and cellular entry mechanisms, and proposes evidence-based prevention and management strategies.

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Memristor-based multi-synaptic spiking neuron circuit for spiking neural network

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Chinese Physics B 2022年第4期31卷 225-233页

作者： Wenwu Jiang Jie Li Hongbo Liu Xicong Qian Yuan Ge Lidan Wang Shukai Duan College of Artificial Intelligence Southwest UniversityChongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China

Spiking neural networks(SNNs) are widely used in many fields because they work closer to biological ***,due to its computational complexity,many SNNs implementations are limited to computer ***,this paper proposes a multi-synaptic circuit(MSC) based on memristor,which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse *** synapse circuit participates in the calculation of the network while transmitting the pulse signal,and completes the complex calculations on the software with ***,a new spiking neuron circuit based on the leaky integrate-and-fire(LIF) model is designed in this *** amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as *** combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron(MSSN).The MSSN was simulated in PSPICE and the expected result was obtained,which verified the feasibility of the ***,a small SNN was designed based on the mathematical model of *** the SNN is trained and optimized,it obtains a good accuracy in the classification of the IRIS-dataset,which verifies the practicability of the design in the network.

关键词： memristor multi-synaptic circuit spiking neuron spiking neural network(SNN)

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Communication Jamming of High Power Microwave Pulse to UAV 24

Communication Jamming of High Power Microwave Pulse to UAV

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Song, Ruilong Zheng, Jingzhi Zhang, Mingwen Chen, Xu Ma, Chunguang Lu, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

High power microwave pulse (HPMP) is an effective way to anti unmanned aerial vehicle (UAV), and the jamming of frequency hopping (FH) communication is the best starting point to achieve anti UAV. This paper uses DJI Phantom 4 Pro as the research object and analyzed the relationship between the power, pulse width and duty cycle of HPMP to achieve the jamming of FH communication of the UAV based on its FH communication characteristics, and the reliability of the analysis is verified through experiments. This paper can provide a good idea for the design of an anti UAV scheme based on HPM. © 2023 IEEE.

关键词： Jamming

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MMW Broadband Radar Compressed Sensing Imaging Based on SAMP Optimization Algorithm 24

MMW Broadband Radar Compressed Sensing Imaging Based on SAMP...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Zhou, Jinghan Ma, Chunguang Liu, Jiaming Yuan, Zhenqian Luo, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

With the development of gyrotron traveling wave amplifier, long-range high-resolution millimeterwave (MMW) imaging broadband radar has been developed rapidly. Nyquist theorem brings challenges to wideband radar signal sampling, and the hardware complexity and cost of the required equipment will increase significantly. Compression sensing (CS) takes advantage of the sparsity of the signal in the transformation domain. Under the condition that it is far less than Nyquist sampling rate, it uses random sampling to obtain discrete samples of the signal, and then perfectly reconstructs the signal through nonlinear reconstruction algorithm. This paper proposes a linear majorization sparsity adaptive matching pursuit (LMSAMP) algorithm based on CS theory. The LMSAMP algorithm with adaptive optimization step size selection is used to reconstructed two-dimensional image of wideband MMW radar. The imaging results show that LMSAMP algorithm has a good imaging effect. © 2023 IEEE.

关键词： Radar imaging

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A Conformal AMC-Backed Array of Moderate Gain, Broad Coverage and Wide Bandwidth 12

A Conformal AMC-Backed Array of Moderate Gain, Broad Coverag...

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12th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2024

作者： Ding, Chuanfei Gao, Xiang Liu, Heng Bu, Xiangyuan An, Jianping Beijing Institute of Technology School of Information and Electronics Beijing100081 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing100081 China

ISBN: (纸本)9798350351019

This paper presents a conformal array antenna for emergency communication applications. The array consists of six conformal AMC-backed Yagi antennas, for which approximately half-space beam coverage can be achieved via one-dimensional full-azimuthal beam switching. The Yagi antenna is comprised of a bowtie-shaped driven dipole and three directors with optimized lengths and spacing to achieve the desired radiation characteristics. To increase the gain and generate the oblique directional beam, the Yagi antenna is backed by an AMC reflector. To validate the design, a prototype of conformal array element was fabricated and measured. Experimental results have shown the proposed conformal antenna exhibit a bandwidth of 570 MHz at the 2.4-GHz band, a gain of 7.5 dBi and approximately half-space beam coverage. The superior performance has shown its huge potential in balloon-based emergency communication stations. © 2024 IEEE.

关键词： Microwave antennas

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