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2nd Advanced Imaging and Information Processing Conference, AIIP 2024

作者： Cheng, Xukun Yu, Xuelian Wang, Zhengxian Yin, Hao Zhao, Lihang Li, Jia Niu, Jia Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China Shanxi Key Laboratory of Quantum Information and Quantum Optoelectronic Devices School of Physics Xi’an Jiaotong University Xi’an710049 China Daheng New Epoch Technology Inc. Beijing100085 China

ISBN: (纸本)9781510683068

Spectral resolution is crucial for achieving precise and high-quality imaging and analysis in imaging systems. Coded aperture correlation holography system face challenges in distinguishing objects at different wavelengths due to their limited spectral resolution. This paper presents a method that combines Bessel beams with a lens phase mask to encode an object's spatial and spectral information into a hologram. Reconstruction is achieved by cross-correlating with the point spread hologram for each wavelength, enabling precise imaging under multi-wavelength conditions. Simulation results show that this method only requires recording a single object hologram at the same wavelength, eliminating the need for multiple recordings. It also offers high spectral sensitivity and spectral resolution. This method is expected to further advance the application of spectral imaging technology in fields such as high-resolution imaging and microscopic endoscopy. © 2024 SPIE.

关键词： Holograms

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Primary User Adversarial Attacks on Deep Learning-Based Spectrum Sensing and the Defense Method

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China communications 2021年第12期18卷 94-107页

作者： Shilian Zheng Linhui Ye Xuanye Wang Jinyin Chen Huaji Zhou Caiyi Lou Zhijin Zhao Xiaoniu Yang Science and Technology on Communication Information Security Control Laboratory Jiaxing314000China College of Information Engineering Zhejiang University of TechnologyHangzhou310012China Institute of Cyberspace Security Zhejiang University of TechnologyHangzhou310012China School of Communication Engineering Hangzhou Dianzi UniversityHangzhou310018China

The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been *** this paper,we propose primary user adversarial attack(PUAA)to verify the robustness of the deep learning based spectrum sensing *** adds a care-fully manufactured perturbation to the benign primary user signal,which greatly reduces the probability of detection of the spectrum sensing *** design three PUAA methods in black box *** or-der to defend against PUAA,we propose a defense method based on autoencoder named *** apply the long short-term memory network and the convolutional neural network together to DeepFilter,so that it can extract the temporal and local features of the input signal at the same time to achieve effective *** experiments are conducted to eval-uate the attack effect of the designed PUAA method and the defense effect of *** show that the three PUAA methods designed can greatly reduce the probability of detection of the deep learning-based spectrum sensing *** addition,the experimen-tal results of the defense effect of DeepFilter show that DeepFilter can effectively defend against PUAA with-out affecting the detection performance of the model.

关键词： spectrum sensing cognitive radio deep learning adversarial attack autoencoder defense

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Two Algorithms Based on Iterative Optimization for UAV Path Planning

Two Algorithms Based on Iterative Optimization for UAV Path ...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Biao Chen Shengming Li Zongyang Lv School of Control Science and Engineering Dalian University of Technology Dalian China School of Information and Communication Engineering Dalian University of Technology Dalian China

In this paper, we propose two algorithms based on iterative optimization for UAV path planning. In the first one, a nonlinear programming (NLP) problem of unmanned aerial vehicle (UAV) path planning is transformed into a general quadratically constrained quadratic programming (QCQP) problem by a numerical optimization method and solved through iteration. This method can converge to the optimal solution without giving the initial value. It overcomes the problems that NLP solvers are dependent on the initial guess, slow to converge, and sometimes can't converge to a feasible solution. In the second one, we improve the optimized rapidly exploring random tree algorithm (RRT*) and add UAV flight constraints to it. The improved RRT* algorithm reduces the length of the path and makes the path smoother.

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Receiver System Design for Universal Polyphase DFT Digital Channelization Algorithm 5

Receiver System Design for Universal Polyphase DFT Digital C...

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5th IEEE International Conference on Electronics technology, ICET 2022

作者： Lu, Shihang Su, Zhengyu Liao, Kaisheng Li, Chao Xiao, Zhuoling Yan, Bo Lin, Shuisheng Wu, Bo University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory National Key Laboratory of Science and Technology on Blind Signal Processing School of Information and Communication Engineering China

ISBN: (纸本)9781665485081

Receiver plays a vital role in various electronic countermeasure systems and has always been a hot topic to research. Based on the traditional receiver digital channelization structure, this paper further researches and derives the high-efficiency digital channelization structure based on polyphase discrete Fourier transform corresponding to various application scenarios. Then we design a 256-sub-channel digital channelization system and implement it on a 64-channel parallel digital down converter to verify the structure. The system design relies on system on chip as the platform, and we verify the feasibility of it on field programmable gate array. © 2022 IEEE.

关键词： System-on-chip

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Cuboid-Net: A Multi-Branch Convolutional Neural Network for Joint Space-Time Video Super Resolution

arXiv

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arXiv 2024年

作者： Fu, Congrui Yuan, Hui Xu, Hongji Zhang, Hao Shen, Liquan School of Information Science and Engineering Shandong University Qingdao China School of Control Science and Engineering Shandong University Jinan China School of Information and Control Engineering Qingdao University of Technology Qingdao China School of Communication and Information Engineering Shanghai University Shanghai China

The demand for high-resolution videos has been consistently rising across various domains, propelled by continuous advancements in science, technology, and societal. Nonetheless, challenges arising from limitations in imaging equipment capabilities, imaging conditions, as well as economic and temporal factors often result in obtaining low-resolution images in particular situations. Space-time video super-resolution aims to enhance the spatial and temporal resolutions of low-resolution and low-frame-rate videos. The currently available space-time video super-resolution methods often fail to fully exploit the abundant information existing within the spatio-temporal domain. To address this problem, we tackle the issue by conceptualizing the input low-resolution video as a cuboid structure. Drawing on this perspective, we introduce an innovative methodology called "Cuboid-Net," which incorporates a multi-branch convolutional neural network. Cuboid-Net is designed to collectively enhance the spatial and temporal resolutions of videos, enabling the extraction of rich and meaningful information across both spatial and temporal dimensions. Specifically, we take the input video as a cuboid to generate different directional slices as input for different branches of the network. The proposed network contains four modules, i.e., a multi-branch-based hybrid feature extraction (MBFE) module, a multi-branch-based reconstruction (MBR) module, a first stage quality enhancement (QE) module, and a second stage cross frame quality enhancement (CFQE) module for interpolated frames only. Experimental results demonstrate that the proposed method is not only effective for spatial and temporal super-resolution of video but also for spatial and angular super-resolution of light field. Copyright © 2024, The Authors. All rights reserved.

关键词： Extraction

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High-fidelity parametric amplification of Ince–Gaussian beams

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Chinese Optics Letters 2022年第11期20卷 105-109页

作者： Ding Yan Zhiyuan Zhong Tong Qi Hongying Chen Wei Gao Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication EngineeringHarbin University of Science and TechnologyHarbin 150080China

Ince–Gaussian (IG) beams, as eigenfunctions of the paraxial wave equation in elliptical coordinates, are attracting increasing interest owing to their propagation-invariant and full-field properties. Optical amplification via parametric interactions can further expand their application areas, yet it is rarely studied. In this work, we report on a high-fidelity parametric amplifier for IG beams. The nonlinear transformation of the spatial spectra of the signal and associated influences on the beam profiles of the amplified signal, under different pump structures, were theoretically and experimentally investigated. By using a perfect flattop beam as the pump, we show that the transverse structure of IG signals is well maintained,and the distortion induced by radial-mode degeneration is overcome during amplification. This proof-of-principle demonstration paves the way for a mode-independent and distortion-free amplifier of arbitrary structured light and has great significance in relevant areas, such as quantum optics, tunable infrared-laser generation, and image amplification.

关键词： optical parametric amplification Ince–Gaussian beam high fidelity perfect flattop beam

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Transceivers Design for Slow-Time Cross Ambiguity Function Shaping

Transceivers Design for Slow-Time Cross Ambiguity Function S...

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European Signal Processing Conference (EUSIPCO)

作者： Tao Fan Yi Wang Xianxiang Yu Guolong Cui Wenmin Wang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

This paper deals with the joint design of slow-time code and receive filters at uncertain ranges for cross ambiguity function (CAF) shaping to mitigate the disturbance power robustly. The weighted interference power at the output of the filters is minimized along with the modulus constraint and signal-to-noise ratio (SNR) loss constraints. To tackle the resultant non-convex optimization problem, an iterative algorithm based on alternating direction penalty method (ADPM) is developed, in which the subproblems involved in each iteration with closed-form solutions. Numerical simulations demonstrate the interference suppression capability of the proposed algorithm.

关键词： Filters Uncertainty Codes Target tracking Signal processing algorithms Radar tracking Transceivers Radar signal processing Iterative methods Signal to noise ratio

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Bit-Level Composite Signal Design for Simultaneous Ranging and communication

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China communications 2021年第6期18卷 214-227页

作者： Weigang Chen Yalong He Changcai Han Jinsheng Yang Zhan Xu School of Microelectronics Tianjin UniversityTianjin 300072China Key Laboratory of Modern Measurement and Control Technology Beijing 100192China School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100192China

As the complexity of space exploration missions augments,how to enhance the overall performance of communication,ranging or other functions has become a challengeable *** the integration of communication and ranging,we present a bit-level composite signal for simultaneous ranging and *** this composite method,through a specially designed mapping scheme using low-weight codewords,the information sequence is converted to a sparse sequence which is then superimposed on the ranging *** ranging,the correlation characteristics of the ranging code component can be maintained to calculate the transmitter-receiver *** communications,the sparse sequence can be extracted without interference by eliminating the ranging code *** results show that the proposed composite signal can support communication and ranging simultaneously with limited sacrifice of ranging performance,and the performance loss of ranging can be controlled and minimized by lowering the density of information sequences using different sparsification encoding methods.

关键词： composite signal spectrum sharing lowweight codeword regenerative PN ranging code

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DSAC-T Based Resource Allocation Strategy for Delay Minimization in RIS-Aided MEC Networks

DSAC-T Based Resource Allocation Strategy for Delay Minimiza...

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IEEE Conference on Wireless communications and Networking

作者： Tianyu Pang Fuhao Liu Xinpei Chen Jiansong Miao Junsheng Mu Zaodi Song School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China North Automatic Control Technology Institute Taiyuan China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

With the explosive growth of user data in 6G networks, existing infrastructures face significant scalability and latency challenges. Mobile Edge Computing (MEC) partially alleviates these issues by deploying computational resources closer to users, but still struggles to fully meet the growing demands. Re-configurable Intelligent Surfaces (RIS) enhance communication performance by improving channel quality. However, optimizing resource allocation in RIS-aided MEC systems remains a critical challenge due to the complexity of real-time optimization of multiple parameters. Although Deep Reinforcement Learning (DRL) methods like Deep Deterministic Policy Gradient (DDPG) have been applied, they often suffer from Q-value overestimation and instability, resulting in suboptimal performance in dynamic environments. This paper focuses on a single-cell RIS-aided MEC network where multiple user devices offload computational tasks to an edge server. We propose an optimized resource allocation scheme using an improved Distributed Soft Actor-Critic (DSAC-T) algorithm. This approach jointly optimizes power control, computation offloading, edge computing resource allocation, and RIS phase shifts, aiming to minimize total offloading delay to ensure real-time service requirements. Simulation results demonstrate that DSAC-T outperforms multiple baseline methods (e.g., DDPG and SAC) in reducing offloading delay by 46.39% and 16.70%, respectively, while significantly enhancing system stability and convergence speed.

关键词： Heuristic algorithms Simulation Power control Stability analysis Real-time systems Delays Resource management Servers Optimization Convergence

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Flame region segmentation of a coal-fired power plant boiler burner through YOLOv8-MAH model

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Fuel 2025年 398卷

作者： Pu, Sixu Li, Jian Han, Zhezhe Zhu, Xiaoyu Xu, Chuanlong National Engineering Research Center of Power Generation Control and Safety School of Energy and Environment Southeast University Nanjing China School of Communication and Artificial Intelligence Nanjing Institute of Technology Nanjing China

Effective segmentation of flame regions in coal-fired power plant boiler burners is critical for enhancing combustion monitoring and operational safety. Traditional methods often suffers from the interference of complicated furnace environments, such as furnace background, adjacent burners and fly ash. This study introduces an advanced flame segmentation approach utilizing the YOLOv8 framework, improved by a multi-level augment head (MAH) and single-object tracking techniques to integrate shallow and deep feature information. Moreover, a convolutional block attention module (CBAM) is embedded in the backbone network to refine feature extraction, while the reparameterization and cross-stage feature reuse are applied in the neck network to bolster multi-scale feature fusion. Experimental results demonstrate that the improved model achieves a mean intersection over union (mIoU) of 82.6—an 8.8 increase over the original YOLOv8—while maintaining high computational efficiency with an inference time of 4.43 ms. Compared with other semantic segmentation models, the proposed model achieves superior accuracy and inference speed. Its performance is validated on a 660 MW opposed-fired boiler, where it can mitigate external disturbances and effectively segment the flame regions under varying load conditions. This method provides a reliable foundation for image-based flame detection systems, enabling real-time and precise monitoring of combustion conditions. © 2025 Elsevier Ltd

关键词： Semantic Segmentation

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