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Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

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Chinese Physics B 2024年第5期33卷 306-314页

作者：丁大为牛炎张红伟杨宗立王金王威王谋媛 school of electronics and information engineering Anhui UniversityHefei 230601China

This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network(FRHNN),utilizing memristors for emulating neural *** study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams,Lyapunov exponents(LEs),and bifurcation ***,the parameter related firing behaviors are described through two-parameter bifurcation ***,local attraction basins reveal multi-stability phenomena related to initial ***,the proposed model is implemented on a microcomputer-based ARM platform,and the experimental results correspond to the numerical ***,the article explores the application of digital watermarking for medical images,illustrating its features of excellent imperceptibility,extensive key space,and robustness against attacks including noise and cropping.

关键词： fractional order memristors Rulkov neuron medical image watermarking

A novel Bayesian-based INS/GNSS integrated positioning method with both adaptability and robustness in urban environments

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Chinese Journal of Aeronautics 2024年第6期37卷 205-218页

作者： Zhe YANG Hongbo ZHAO school of electronics and information engineering Beihang UniversityBeijing 100191China

Achieving higher accuracy positioning results in urban environments at a lower cost has been an important pursuit in areas such as autonomous driving and intelligent *** Inertial Navigation System and Global Navigation Satellite System(INS/GNSS)integrated navigation systems have been an important means of fulfilling the above quest due to the complementary error characteristics between INS and *** complex urban driving environment requires the system sufficiently adaptive to keep up with the time-varying measurement noise and sufficiently robust to cope with measurement outliers and prior ***,many efforts lack a balance between adaptability and *** this paper,a novel positioning method with both adaptability and robustness is proposed by coupling the Mahalanobis distance method,the Variational Bayesian method and the student’s t-distribution in one process(M-VBt method).This method is robust against non-Gaussian noise and priori uncertainties,plus adaptive against measurement noise uncertainty and time-varying *** field test results show that the M-VBt method(especially the Mahalanobis distance part)has significantly improved the system performance in the complex urban driving environment.

关键词： Urban environments Mahalanobis distance Adaptability Robustness Integrated navigation

A whole-net cooperative positioning method based on CDGNSS and inter-vehicle ranging

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Chinese Journal of Aeronautics 2024年第2期37卷 401-416页

作者： Shan HU Hongbo ZHAO Chen ZHUANG school of electronics and information engineering Beihang UniversityBeijing 100191China

Relative positioning is recognized as an important issue for vehicles in urban ***-vehicle Cooperative Positioning(CP)techniques which fuse the Global Navigation Satellite System(GNSS)and inter-vehicle ranging have attracted attention in improving the performance of baseline estimation between ***,current CP methods estimate the baselines separately and ignore the interactions among the positioning information of different *** interactions are called’information coupling’.In this work,we propose a new multivehicle precise CP framework using the coupled information in the network based on the Carrier Differential GNSS(CDGNSS)and inter-vehicle *** demonstrate the benefit of the coupled information by deriving the Cramer-Rao Lower Bound(CRLB)of the float estimation in *** fully use this coupled information,we propose a Whole-Net CP(WN-CP)method which consists of the Whole-Net Extended Kalman Filter(WN-EKF)as the float estimation filter,and the Partial Baseline Fixing(PBF)as the ambiguity resolution *** WN-EKF fuses the measurements of all baselines simultaneously to improve the performance of float estimation,and the PBF strategy fixes the ambiguities of the one baseline to be estimated,instead of full ambiguity resolution,to reduce the computation load of ambiguity *** tests involving four vehicles were conducted in urban *** results show that the proposed WN-CP method can achieve better performance and meanwhile maintain a low computation load compared to the existing methods.

关键词： GNSS Cooperative positioning Baseline Ambiguity resolution information coupling

Client selection and resource scheduling in reliable federated learning for UA V-assisted vehicular networks

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Chinese Journal of Aeronautics 2024年第9期37卷 328-346页

作者： Hongbo ZHAO Liwei GENG Wenquan FENG ChangmingZHOU school of electronics and information engineering Beihang UniversityBeijing 100191China

Federated Learning(FL),a promising deep learning paradigm extensively deployed in Vehicular Edge Computing Networks(VECN),allows a distributed approach to train datasets of nodes locally,e.g.,for mobile vehicles,and exchanges model parameters to obtain an accurate model without raw data ***,the existence of malicious vehicular nodes as well as the inherent heterogeneity of the vehicles hinders the attainment of accurate ***,the local model training and model parameter transmission during FL exert a notable energy burden on vehicles constrained in *** view of this,we investigate FL client selection and resource management problems in FL-enabled UAV-assisted Vehicular Networks(FLVN).We first devise a novel reputation-based client selection mechanism by integrating both data quality and computation capability metrics to enlist reliable high-performance ***,to fortify the FL reliability,we adopt the consortium blockchain to oversee the reputation informa-tion,which boasts tamper-proof and interference-resistant ***,we formulate the resource scheduling problem by jointly optimizing the computation capability,the transmission power,and the number of local training rounds,aiming to minimize the cost of clients while guaranteeing *** this end,we propose a reinforcement learning algorithm employing an asynchronous parallel network structure to achieve an optimized scheduling *** results show that our proposed client selection mechanism and scheduling algorithm can realize reliable FL with an accuracy of 0.96 and consistently outperform the baselines in terms of delay and energy consumption.

关键词： Federated learning Vehicular edge computing Resource management Reinforcement learning Optimization techniques

Intelligent secure near-field communication

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Science China(information Sciences) 2024年第9期67卷 340-341页

作者： Nan ZHANG Jifa ZHANG Chengwen XING Na DENG Nan ZHAO school of information and Communication engineering Dalian University of Technology school of information and electronics Beijing Institute of Technology

The research and development efforts for the sixth generation(6G) wireless communication are underway to fulfill the growing demands for wireless communications. 6G is expected to become the key enabler for diverse new applications and services [1]. To achieve the excellent performance, 6G will implement extremely large-scale antenna arrays(ELAAs), terahertz [2], and new types of antennas with metamaterials, leading to a paradigm shift for the electromagnetic characteristics.

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A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

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Journal of Beijing Institute of Technology 2024年第2期33卷 103-110页

作者： Liting Zhang Hao Huan Ran Tao Xiaogang Tang school of information and electronics Beijing Institute of Technology school of Aerospace information Space Engineering University

Recently, researchers have proposed an emitter localization method based on passive synthetic aperture. However, the unknown residual frequency offset(RFO) between the transmitter and the receiver causes the received Doppler signal to shift, which affects the localization accuracy. To solve this issue, this paper proposes a RFO estimation method based on range migration fitting. Due to the high frequency modulation slope of the linear frequency modulation(LFM)-modulation radar signal, it is not affected by RFO in range compression. Therefore, the azimuth time can be estimated by fitting the peak value position of the pulse compression in range ***, the matched filters are designed under different RFOs. When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time, the given RFO is the real RFO between the transceivers. The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s, the pulse repetition frequency(PRF) of the transmitter radar signal is not less than 1 k Hz, the range detection is not larger than 1 000 km, and the signal noise ratio(SNR) is not less than –5 d B.

关键词： range migration fitting (RMF) passive localization residual frequency offset (RFO)

The Extended Hybrid Carrier-Based Multiple Access Technology for High Mobility Scenarios

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China Communications 2024年第1期21卷 53-68页

作者： Ge Song Xiaojie Fang Xuejun Sha school of electronics and information engineering Harbin Institute of TechnologyHarbin 150001China

The hybrid carrier(HC)system rooted in the carrier fusion concept is gradually garnering *** this paper,we study the extended hybrid carrier(EHC)multiple access scheme to ensure reliable wireless *** employing the EHC modulation,a power layered multiplexing framework is realized,which exhibits enhanced interference suppression capability owing to the more uniform energy distribution *** implementation method and advantage mechanism are explicated respectively for the uplink and downlink,and the performance analysis under varying channel conditions is *** addition,considering the connectivity demand,we explore the non-orthogonal multiple access(NOMA)method of the EHC system and develop the EHC sparse code multiple access *** proposed scheme melds the energy spread superiority of EHC with the access capacity of NOMA,facilitating superior support for massive connectivity in high mobility *** results have verified the feasibility and advantages of the proposed *** with existing HC multiple access schemes,the proposed scheme exhibits robust bit error rate performance and can better guarantee multiple access performance in complex scenarios of nextgeneration communications.

关键词： extended hybrid carrier system high mo-Received:Jun.09,2023 Revised:Nov.20,2023 Editor:Yuanwei Liu bility communications multiple access

Effects of quantum noise on teleportation of arbitrary two-qubit state via five-particle Brown state

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Chinese Physics B 2024年第8期33卷 204-211页

作者：汪澳魏玉震姜敏李泳成陈虹黄旭 school of electronics&information engineering Soochow UniversitySuzhou 215006China Key Laboratory of System Control and information Processing Ministry of EducationShanghai 200240China school of information engineering Huzhou UniversityHuzhou 313000China

We propose a new protocol for quantum teleportation(QT)which adopts the Brown state as the quantum *** work focuses on the teleportation of a single unknown two-qubit state via a Brown state channel in an ideal *** validate the effectiveness of our proposed scheme,we conduct experiments by using the quantum circuit simulator ***,we investigate the effects of four noisy channels,namely,the phase damping noise,the bit-flip noise,the amplitude damping noise,and the phase-flip ***,we employ Monte Carlo simulation to elucidate the fidelity density under various noise *** analysis demonstrates that the fidelity of the protocol in a noisy environment is influenced significantly by the amplitude of the initial state and the noise factor.

关键词： quantum communication Brown state fidelity

Controlling underestimation bias in reinforcement learning via minmax operation

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Chinese Journal of Aeronautics 2024年第7期37卷 406-417页

作者： Fanghui HUANG Yixin HE Yu ZHANG Xinyang DENG Wen JIANG school of electronics and information Northwestern Polytechnical UniversityXi’an 710129China College of information Science and engineering Jiaxing UniversityJiaxing 314001China

Obtaining the accurate value estimation and reducing the estimation bias are the key issues in reinforcement ***,current methods that address the overestimation problem tend to introduce underestimation,which face a challenge of precise decision-making in many *** address this issue,we conduct a theoretical analysis of the underestimation bias and propose the minmax operation,which allow for flexible control of the estimation ***,we select the maximum value of each action from multiple parallel state-action networks to create a new state-action value ***,a minimum value is selected to obtain more accurate value ***,based on the minmax operation,we propose two novel algorithms by combining Deep Q-Network(DQN)and Double DQN(DDQN),named minmax-DQN and ***,we conduct theoretical analyses of the estimation bias and variance caused by our proposed minmax operation,which show that this operation significantly improves both underestimation and overestimation biases and leads to the unbiased ***,the variance is also reduced,which is helpful to improve the network training ***,we conduct numerous comparative experiments in various environments,which empirically demonstrate the superiority of our method.

关键词： Reinforcement learning Minmax operation Estimation bias Underestimation bias Variance