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Parameter estimation in n-dimensional massless scalar field

Chinese Physics B 2024年第3期33卷 231-237页

作者：杨颖荆继良 Hunan Provincial Key Laboratory of Intelligent Sensors and Advanced Sensor Materials School of Physics and ElectronicsHunan University of Science and TechnologyXiangtan 411201China Department of Physics Key Laboratory of Low Dimensional Quantum Structures and Quantum Control of Ministry of Educationand Synergetic Innovation Center for Quantum Effects and ApplicationsHunan Normal UniversityChangsha 410081Chin

Quantum Fisher information(QFI)associated with local metrology has been used to parameter estimation in open quantum *** this work,we calculated the QFI for a moving Unruh-DeWitt detector coupled with massless scalar fields in n-dimensional spacetime,and analyzed the behavior of QFI with various parameters,such as the dimension of spacetime,evolution time,and Unruh *** discovered that the QFI of state parameter decreases monotonically from 1 to 0 over ***,we noted that the QFI for small evolution times is several orders of magnitude higher than the QFI for long evolution *** also found that the value of QFI decreases at first and then stabilizes as the Unruh temperature *** was observed that the QFI depends on initial state parameterθ,and Fθis the maximum forθ=0 orθ=π,Fφis the maximum forθ=π/*** also obtain that the maximum value of QFI for state parameters varies for different spacetime dimensions with the same evolution time.

关键词： quantum Fisher information parameter estimation open quantum systems

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Research on network intrusion detection based on Whitening PCA and CNN 7

Research on network intrusion detection based on Whitening P...

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7th International Conference on Smart Grid and Smart Cities, ICSGSC 2023

作者： Zhang, Peiqing Tian, Guangke Dong, Haiying Lanzhou Jiaotong University Key Laboratory of Optoelectronic Technology and Intelligent Control of Ministry of Education Lanzhou China Lanzhou Jiaotong University School of New Energy and Power Engineering Lanzhou China

ISBN: (纸本)9798350305913

In the face of a large number of network attacks, intrusion detection system can issue early warning, indicating the emergence of network attacks. In order to improve the traditional machine learning network intrusion detection model to identify the behavior of network attacks, improve the detection accuracy and accuracy. Convolutional neural network is used to construct intrusion detection model, which has better ability to solve complex problems and better adaptability of algorithm. In order to solve the problems such as dimension explosion caused by input data, the albino PCA algorithm is used to extract data features and reduce data dimensions. For the common problem of convolutional neural networks in intrusion detection such as overfitting, Dropout layers are added before and after the fully connected layer of CNN, and Sigmoid is selected as the intrusion classification prediction function. This reduces the overfitting, improves the robustness of the intrusion detection model, and enhances the fault tolerance and generalization ability of the model to improve the accuracy of the intrusion detection model. The effectiveness of the proposed method in intrusion detection is verified by comparison and analysis of numerical examples. © 2023 IEEE.

关键词： Intrusion detection

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Many-to-many GEO on-orbit refueling mission optimization under time-varying fuel demands via modified differential evolution 74

Many-to-many GEO on-orbit refueling mission optimization und...

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74th International Astronautical Congress, IAC 2023

作者： Li, Chuanjiang Han, Peng Zhang, Haibo Guo, Yanning Harbin Institute of Technology China Beijing Institute of Control Engineering National Key Laboratory of Science and Technology on Space Intelligent Control China

As a kind of on-orbit servicing technology, on-orbit refueling (OOR) has essential significance in prolonging the lifetime of satellites and decreasing the generation of space debris, especially for the expensive satellites located in geosynchronous orbit (GEO). Recently, several one-to-one mode-based OOR missions have been successfully conducted in space. To further reduce the economic cost, the mode of using several refuel satellites (RS) to refuel some dozens of client satellites (CS) in one mission has been proposed, that is, the many-to-many OOR mode. To maximize the efficiency of this mode, the mission optimization problem that determines the refueling sequence and time should be further investigated. The mission optimization is usually carried out before the OOR mission starts, and the fuel demand of CS is obtained in advance. However, the OOR mission for multiple GEO CSs usually takes a long time, and some temporarily unrefueled CSs may perform orbit maintenance by consuming the remaining fuel, leading to a time-varying fuel demand change. In this case, performing the initial mission optimization results may lead to efficiency reduction or even mission failure. To address this problem, in this paper, a many-to-many mode-based OOR mission optimization model is established considering the time-varying fuel demands, and a differential evolution (DE) based algorithm is designed to solve the problem. Firstly, a remaining fuel varying law is obtained according to the periodic orbit maintenance strategy of GEO CSs. Based on that, the mission profit model is further established. Then, by additionally considering several constraints like RS fuel capacity, mission duration, and orbital maneuver duration, the mission optimization model is established. Next, by taking the refueling sequence, the instant of refueling begins as the design variable, and a modified DE is designed to solve the problem. Unlike existing DE, a greedy-search-based mechanism generates high-qualit

关键词： differential evolution geosynchronous orbit on-orbit refueling time-varying fuel demands

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Weak signal detection method based on novel composite multistable stochastic resonance

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Chinese Physics B 2023年第5期32卷 178-187页

作者：焦尚彬高蕊薛琼婕史佳强 Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer *** propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable *** with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system *** model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of *** the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is *** application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer *** outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

关键词： weak signal detection composite multistable stochastic resonance bearing fault detection

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Performance analysis of UAV-based mixed underwater PLC-RF systems

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Digital Communications and Networks 2024年第5期10卷 1332-1340页

作者： Shenghai Chen Liang Yang Xianfu Lei College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua418000China School of Information Science and Technology Southwest Jiaotong UniversityChengdu610031China

In this study,we analyzed the performance of an Unmanned Aerial Vehicle(UAV)-based mixed Underwater Power Line Communication-Radio Frequency(UPLC-RF)*** this network,a buoy located at the sea is used as a relay to transmit signals from the underwater signal source to the UAV through the PLC *** assume that the UPLC channel obeys a log-normal distribution and that the RF link follows the Rician *** this model,we obtained the closed-form expressions for the Outage Probability(OP),Average Bit-error-rate(ABER),and Average Channel Capacity(ACC).In addition,the asymptotic analysis of the OP and ABER was performed,and an upper bound for the average capacity was ***,the analytical results were verified by Monte Carlo simulation thereby demonstrating the effect of impulse noise and the altitude of the UAV on network performance.

关键词： ABER Average bit-error-rate ACC Average channel capacity OP Outage probability UAV Unmanned aerial vehicle UPLC Underwater power line communication

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Fast Brillouin frequency shift estimation using digital elevation modeling method in BOTDR 4

Fast Brillouin frequency shift estimation using digital elev...

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4th International Computational Imaging Conference, CITA 2024

作者： Zan, Wei Liu, Xinyi Yang, Mingyuan Bai, Qai Wang, Yu Jin, Baoquan Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education Taiyuan University of Technology Taiyuan030024 China College of Physics and Optoelectronic Engineering Taiyuan University of Technology Taiyuan030024 China College of Electronic Information Engineering Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9781510688834

In the practical application of Brillouin optical time-domain reflectometry (BOTDR) in temperature and strain monitoring, enhancing measurement speed remains a critical challenge. This paper presents a novel method for Brillouin frequency shift (BFS) estimation utilizing level set and digital elevation modeling (DEM). The algorithm demonstrates superior time efficiency. At the same time, the accuracy of the scheme is proved in the comparation experiment and correlation analysis. The method reduces computational time, without spatial resolution or measurement error degradation. © 2025 SPIE.

关键词： Digital elevation model

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Multi-View Joint Target Selection for Relativistic-Perturbed Starlight Navigation

Multi-View Joint Target Selection for Relativistic-Perturbed...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Zhao, Yaru Ge, Dantong Xiong, Kai School of Aerospace Engineering Beijing Institute of Technology Beijing China Key Laboratory of Autonomous Navigation Control for Deep Space Exploration Beijing Institute of Technology Beijing China National Key Laboratory of Space Intelligent Control Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9798350384185

Autonomous navigation is one of the key technologies for spacecraft to realize long-term space operation and carry out science missions. In order to meet the requirement of high precision autonomous navigation, the effects of the gravitational deflection of light, stellar aberration and measurement bias of sensor are considered to establish a relativistic-perturbed starlight navigation scheme. To obtain high quality measurements, a multi-probe star sensor composed of multiple field of view probes is adopted for observation. A polygonal star pair selection method is proposed to conduct multi-view joint target selection. By constructing irregular polygons to select high quality star pair observations, the accuracy of navigation estimation is expected to be improved. The performance of relativistic-perturbed starlight navigation using the multi-view joint target selection method is then verified through a numerical simulation. © 2024 IEEE.

关键词： Probes

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Automatic SOC Equalization Strategy of Energy Storage Units with DC Microgrid Bus Voltage Support

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Energy Engineering 2024年第2期121卷 439-459页

作者： Jingjing Tian Shenglin Mo Feng Zhao Xiaoqiang Chen School of Automation&Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China Key Laboratory of Opto-Technology and Intelligent Control(Lanzhou Jiaotong University) Ministry of EducationLanzhou730070China

In this paper,an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load and PV power variations in a stand-alone DC *** strategy includes primary and secondary *** them,the primary control suppresses the DC microgrid voltage fluctuation through the I and II section control,and the secondary control aims to correct the P-U curve of the energy storage system and the PV system,thus reducing the steady-state bus voltage *** simulation results demonstrate that the proposed control strategy effectively achieves SOC balancing and enhances the immunity of bus *** proposed strategy improves the voltage fluctuation suppression ability by approximately 39.4%and 43.1%under the PV power and load power fluctuation conditions,***,the steady-state deviation of the bus voltage,△U_(dc) is only 0.01–0.1 V,ensuring stable operation of the DC microgrid in fluctuating power environments.

关键词： Automatic equalization independent DC microgrid improve droop control secondary control state of charge

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Protecting Multiple Types of Privacy Simultaneously in EEG-Based Brain-Computer Interfaces

Protecting Multiple Types of Privacy Simultaneously in EEG-B...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Meng, Lubin Jiang, Xue Jia, Tianwang Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9781665410205

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs. © 2024 IEEE.

关键词： Differential privacy

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Research and application of composite stochastic resonance in enhancement detection

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Chinese Physics B 2024年第1期33卷 264-273页

作者：高蕊焦尚彬薛琼婕 School of Automation and Information Engineering Xi'an University of TechnologyXi'an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an 710048China

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance(NCSR) model is proposed by combining the Woods–Saxon(WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation, all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection ***, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio(PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

关键词： Woods–Saxon improved piecewise model composite stochastic resonance(SR) image denoising

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