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Parameter identification of magnetic levitation system based on modulation function method
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作者 Tingchen Du Xueling Fan Sheng Feng 《Control Theory and Technology》 2025年第4期602-617,共16页
A novel parameter identification method for magnetic levitation bearing rotor systems is proposed,based on the modulation function method.The fundamental principle of the modulation function method for parameter ident... A novel parameter identification method for magnetic levitation bearing rotor systems is proposed,based on the modulation function method.The fundamental principle of the modulation function method for parameter identification is derived on the basis of the characteristics of the modulation function.The transformation of the differential equation model of a continuous system into a general algebraic equation model is effectively achieved,thereby avoiding the influence of errors introduced by the initial value and differential derivation of the system.Modulation function method parameter identification models have been established for single-degree-of-freedom and multi-degree-of-freedom magnetic levitation bearing rotor systems.The influence of different parameters of Hartley modulation function on the accuracy of system parameter identification has been investigated,thus providing a basis for the design of Hartley modulation function parameters.Simulation and experimental results demonstrate that the modulation function method can effectively identify system parameters despite the presence of system noise. 展开更多
关键词 modulation function method Hartley modulation function Magnetic levitation system Parameter identification
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Gauss linear frequency modulation wavelet transforms and its application to seismic phases identification
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作者 刘希强 周惠兰 +3 位作者 曹文海 李红 李永红 季爱东 《Acta Seismologica Sinica(English Edition)》 CSCD 2002年第6期636-645,共10页
Based on the characteristics of gradual change style seismic signal onset which has more high frequency signal components but less magnitude, this paper selects Gauss linear frequency modulation wavelet as base functi... Based on the characteristics of gradual change style seismic signal onset which has more high frequency signal components but less magnitude, this paper selects Gauss linear frequency modulation wavelet as base function to study the change characteristics of Gauss linear frequency modulation wavelet transform with difference wavelet and signal parameters, analyzes the error origin of seismic phases identification on the basis of Gauss linear frequency modulation wavelet transform, puts forward a kind of new method identifying gradual change style seismic phases with background noise which is called fixed scale wavelet transform ratio, and presents application examples about simulation digital signal and actual seismic phases recording onsets identification. 展开更多
关键词 Gauss linear frequency modulation wavelet wavelet transform gradual change style seismic sig-nal onset identification
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Radar Signal Intra-Pulse Modulation Recognition Based on Deep Residual Network
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作者 Fuyuan Xu Guangqing Shao +3 位作者 Jiazhan Lu Zhiyin Wang Zhipeng Wu Shuhang Xia 《Journal of Beijing Institute of Technology》 EI CAS 2024年第2期155-162,共8页
In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intr... In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB). 展开更多
关键词 intra-pulse modulation low signal-to-noise deep residual network automatic recognition
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Tree Species Identification and Counting in UAV Optical Images Based on Improved YOLOv8n
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作者 Chenyang HU Jie XU 《Agricultural Biotechnology》 2025年第4期84-87,共4页
Forests play a crucial role in ecosystems.This study focused on five common tree species in Northeast China:pine,elm,poplar,cedar,and ash.An improved YOLOv8n-based network structure was constructed,and a UAV image dat... Forests play a crucial role in ecosystems.This study focused on five common tree species in Northeast China:pine,elm,poplar,cedar,and ash.An improved YOLOv8n-based network structure was constructed,and a UAV image dataset was developed for analysis.The results showed that the improved YOLOv8 algorithm achieved a 4.9%increase in accuracy compared with the original version,and the average precision increased from 88.0%(original YOLOv8n)to 92.1%. 展开更多
关键词 YOLOv8n UAV modulE Tree species identification
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Specific emitter identification based on frequency and amplitude of the signal kurtosis
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作者 ZHAO Yurui WANG Xiang +1 位作者 SUN Liting HUANG Zhitao 《Journal of Systems Engineering and Electronics》 2025年第2期333-343,共11页
Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint featur... Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method. 展开更多
关键词 communication emitter fingerprint feature KURTOSIS unintentional modulation(UIM) specific emitter identification(SEI).
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Link Budget Design with Performance Evaluation of Tunable Impulse-Based Ultra Wideband to Support the Integration of Wireless Sensing and Identifications Infrastructures 被引量:1
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作者 Mohammed Seed Jawad Widad Ismail +2 位作者 Ayman Hajjawi Othman Abdul Rani Azahari Saleh 《Journal of Sensor Technology》 2014年第3期127-138,共12页
Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting t... Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting these advantages of IR-UWB technology at the physical-layer design, this paper proposes that a cross layer architecture platform can be considered as a good integrator for different wireless short-ranges indoor protocols into a universal smart wireless-tagged architecture with new promising applications in cognitive radio for future applications. Adaptive transmission algorithms have been studied to show the trade-off between different specific QoS requirements, transmission rates and distances at the physical layer level and this type of dynamic optimization and reconfiguration leads to the cross-layer design proposal in the paper. Studies from both theoretical simulation and statistical indoor environments experiments are considered as a proof of concept for the proposed architecture. 展开更多
关键词 RADIO Frequency identification (RFID) ULTRA-WIDEBAND (UWB) Impulse-Based ULTRA-WIDEBAND (IR-UWB) Cognitive RADIO (CR) Time Hopping Pulse Position modulation (TH-PPM) Quality of Service (QoS)
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New modal identification method under the non-stationary Gaussian ambient excitation
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作者 杜秀丽 汪凤泉 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2009年第10期1295-1304,共10页
Based on the multivariate continuous time autoregressive (CAR) model, this paper presents a new time-domain modal identification method of linear time-invariant system driven by the uniformly modulated Gaussian rand... Based on the multivariate continuous time autoregressive (CAR) model, this paper presents a new time-domain modal identification method of linear time-invariant system driven by the uniformly modulated Gaussian random excitation. The method can identify the physical parameters of the system from the response data. First, the structural dynamic equation is transformed into a continuous time autoregressive model (CAR) of order 3. Second, based on the assumption that the uniformly modulated function is approximately equal to a constant matrix in a very short period of time and on the property of the strong solution of the stochastic differential equation, the uniformly modulated function is identified piecewise. Two special situations are discussed. Finally, by virtue of the Girsanov theorem, we introduce a likelihood function, which is just a con- ditional density function. Maximizing the likelihood function gives the exact maximum likelihood estimators of model parameters. Numerical results show that the method has high precision and the computation is efficient. 展开更多
关键词 modal identification uniformly modulated function continuous time autoregressive model Brownian motion exact maximum likelihood estimator
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Acoustic wireless communication based on parameter modulation and complex Lorenz chaotic systems with complex parameters and parametric attractors
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作者 Fang-Fang Zhang Rui Gao Jian Liu 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第8期248-259,共12页
As the competition for marine resources is increasingly fierce,the security of underwater acoustic communication has attracted a great deal of attention.The information and location of the communicating platform can b... As the competition for marine resources is increasingly fierce,the security of underwater acoustic communication has attracted a great deal of attention.The information and location of the communicating platform can be leaked during the traditional underwater acoustic communication technology.According to the unique advantages of chaos communication,we put forward a novel communication scheme using complex parameter modulation and the complex Lorenz system.Firstly,we design a feedback controller and parameter update laws in a complex-variable form with rigorous mathematical proofs(while many previous references on the real-variable form were only special cases in which the imaginary part was zero),which can be realized in practical engineering;then we design a new communication scheme employing parameter modulation.The main parameter spaces of the complex Lorenz system are discussed,then they are adopted in our communication scheme.We also find that there exist parametric attractors in the complex Lorenz system.We make numerical simulations in two channels for digital signals and the simulations verify our conclusions. 展开更多
关键词 parameter modulation identification chaotic system acoustic wireless communication
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基于多端口断路器的柔直配电系统故障性质辨识与恢复方案
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作者 戴志辉 石浚阳 +3 位作者 李毅然 李涵伟 张轩毅 杨淳皓 《电力系统保护与控制》 北大核心 2026年第1期105-116,共12页
针对柔直系统故障后盲目重合闸造成二次过流冲击及故障恢复期间电流波动导致恢复缓慢问题,提出一种基于多端口断路器的柔直配电系统故障性质辨识与恢复方案。首先,分析了集成多功能潮流控制模块的多端口断路器拓扑结构,通过合并功能相... 针对柔直系统故障后盲目重合闸造成二次过流冲击及故障恢复期间电流波动导致恢复缓慢问题,提出一种基于多端口断路器的柔直配电系统故障性质辨识与恢复方案。首先,分析了集成多功能潮流控制模块的多端口断路器拓扑结构,通过合并功能相同与结构相似的冗余单元,提升设备集成度与经济性。然后,通过控制该模块向故障线路主动注入电流信号辨识故障性质,并构建动态权重可自适应调整的加权组合判据,提高辨识可靠性。故障恢复阶段利用模块自身潮流控制能力削减线路两端换流站出口电压差产生的暂态电流冲击,同时提升系统恢复后对于潮流变化的动态响应能力。最后,在PSCAD/EMTDC建立环状柔直配电网模型进行仿真分析,验证所提方案具有故障辨识可靠性高、功能集成度好、适用场景广泛等优点。 展开更多
关键词 故障性质辨识 故障恢复 多功能潮流控制模块 多端口直流断路器 柔直配电系统
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基于人体部位信息辅助的行人重识别方法
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作者 赵炳涛 张继 +1 位作者 储开斌 王洪元 《计算机科学与探索》 北大核心 2026年第3期865-877,共13页
遮挡问题是行人重识别领域的关键挑战,尤其在复杂背景、多视角和动态场景下,容易导致行人特征信息缺失,严重影响模型的判别能力。针对上述挑战,在全尺度网络(OSNet)基础上,提出一种融合人体部位信息的多尺度行人重识别模型,以提升网络... 遮挡问题是行人重识别领域的关键挑战,尤其在复杂背景、多视角和动态场景下,容易导致行人特征信息缺失,严重影响模型的判别能力。针对上述挑战,在全尺度网络(OSNet)基础上,提出一种融合人体部位信息的多尺度行人重识别模型,以提升网络在遮挡场景下的识别精度。该模型在特征提取阶段引入多尺度混合注意力残差块,结合CBAM与EMA注意力机制对不同尺度的特征进行动态加权,增强关键区域的表示能力;在特征匹配阶段,引入人体部位注意力模块与全局-局部特征学习模块,对行人图像中的可见人体部位进行检测、评分及动态加权融合,有效规避被遮挡区域对匹配结果的干扰。在三个有遮挡的公开数据集Occluded_Duke、Occluded_REID与P-DukeMTMCreID上对所提方法进行了系统评估。在Occluded_Duke数据集上,改进模型的mAP提升20.5个百分点,Rank-1提升22.2个百分点;在其余两个数据集上,mAP和Rank-1指标也分别达到70.1%、78.2%与81.3%、91.0%,显著优于原始模型。实验结果充分验证了所提方法在遮挡场景下的有效性与先进性,为复杂场景下的行人重识别任务提供了一种有效的解决方案,具有重要的应用价值。 展开更多
关键词 行人重识别 多尺度混合注意力残差块 人体部位注意力模块 动态加权融合
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基于一维深度可分离卷积的轻量化辐射源识别
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作者 孙文鑫 孟华 +1 位作者 杨佳煌 周礼亮 《太赫兹科学与电子信息学报》 2026年第1期89-97,共9页
针对深度神经网络的辐射源个体识别技术,为达到良好的识别性能,网络深度不断增加,致使模型参数量与计算复杂度爆炸式增长,难以在边缘端算力受限的设备上部署。为此,本文提出基于一维深度可分离卷积和一维卷积块注意力模块的网络(ODCNet... 针对深度神经网络的辐射源个体识别技术,为达到良好的识别性能,网络深度不断增加,致使模型参数量与计算复杂度爆炸式增长,难以在边缘端算力受限的设备上部署。为此,本文提出基于一维深度可分离卷积和一维卷积块注意力模块的网络(ODCNet)架构,通过结合逐深度卷积和逐点卷积,一维深度可分离卷积有效减少了模型的参数量和计算复杂度;轻量级的一维卷积块注意力模块可有效提升模型性能,保障模型的识别能力。实验表明,ODCNet的识别性能与MobileNet V3相当,而参数量仅为MobileNet V3的11.27%,计算复杂度为MobileNet V3的17.49%,推理时间缩短至MobileNet V3的50%。 展开更多
关键词 辐射源识别 模型轻量化 深度可分离卷积 卷积块注意力模块
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基于改进基频调制电流源换流器的HVDC故障电流抑制策略
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作者 冯定腾 熊小玲 +3 位作者 姚辰昊 周子涵 王胜威 赵成勇 《电力系统自动化》 北大核心 2026年第1期157-167,共11页
改进基频调制电流源换流器(EFFM-CSC)作为基于全控型集成门极换流晶闸管(IGCT)器件的电流源换流器,具有拓扑结构简单、体积重量小、谐波特性好和有功/无功功率灵活可调的优点,受到了广泛关注。然而,基于EFFM-CSC的高压直流(HVDC)系统同... 改进基频调制电流源换流器(EFFM-CSC)作为基于全控型集成门极换流晶闸管(IGCT)器件的电流源换流器,具有拓扑结构简单、体积重量小、谐波特性好和有功/无功功率灵活可调的优点,受到了广泛关注。然而,基于EFFM-CSC的高压直流(HVDC)系统同样面临直流线路短路这一严重故障,目前尚缺乏系统性的定量分析和研究。因此,针对EFFM-CSC换流站拓扑以及短路瞬间开关状态,建立了复频域下的运算电路模型。然后,根据储能等效原则得到等效RLC参数,构建直流短路时EFFM-CSC的故障等值模型,推导出直流故障电流解析计算公式,并讨论了系统参数和故障时刻对故障电流的影响。根据EFFM-CSC直流短路故障特性,提出了一种故障识别判据和故障电流抑制策略,并对抑制策略的控制参数进行整定。最后,基于仿真分析验证了所提故障电流计算方法和故障抑制策略的正确性。 展开更多
关键词 电流源换流器 改进基频调制 高压直流 短路 故障识别 故障电流抑制
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基于动态时空适应图神经网络的电网线路参数辨识方法
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作者 杨秀 傅骞 +3 位作者 汤波 陈宏福 韩政 王治华 《中国电机工程学报》 北大核心 2026年第1期142-156,I0011,共16页
线路参数的准确辨识对于电网的稳定运行与优化至关重要。随着人工智能技术的快速发展,以深度学习为代表的电网线路参数辨识技术在辨识有效性和鲁棒性上具备显著优势,但这些方法往往忽视网架分支的历史趋势和拓扑关系,导致模型未能充分... 线路参数的准确辨识对于电网的稳定运行与优化至关重要。随着人工智能技术的快速发展,以深度学习为代表的电网线路参数辨识技术在辨识有效性和鲁棒性上具备显著优势,但这些方法往往忽视网架分支的历史趋势和拓扑关系,导致模型未能充分学习到关键的时空信息,进一步造成参数辨识精度的下降。为此,提出一种基于动态时空适应图神经网络的电网线路参数辨识方法。首先,关注传统的特征选择和手动调参方法过于依赖专家经验的局限,结合最大信息系数和基于树形结构Parzen估计器的贝叶斯优化技术,对模型超参数进行调优的同时,自动筛选出对电网参数辨识性能贡献最大的SCADA系统量测特征;进一步,依据支路历史特征及电网拓扑信息,构建适用于输电线路参数辨识任务的时空图数据集,利用图卷积网络和时间卷积网络提取图数据集中线路的时空特征,结合动态时空适应模块,精确学习每条线路在不同辨识场景下的独特时空行为。这些组件整合构成了一个高效全面的电网线路参数辨识模型;最后,在IEEE 39节点系统上搭建多种量测场景,并进行算例分析。与现有算法相比,所提方法在应对量测噪声、数据缺失以及多拓扑变化的场景下展示了更优的辨识精度和鲁棒性。 展开更多
关键词 电网线路参数辨识 时空信息融合 最大信息系数 贝叶斯优化 图卷积网络 时间卷积网络 动态时空适应模块
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A novel modulation format identification based on amplitude histogram space
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作者 Tianliang WANG Xiaoying LIU 《Frontiers of Optoelectronics》 EI CSCD 2019年第2期190-196,共7页
In this paper, we proposed a novel modulation format identification method for square M-quadrature amplitude modulation (M-QAM) signals which is based on amplitude histogram space of the incoming data after analog-to-... In this paper, we proposed a novel modulation format identification method for square M-quadrature amplitude modulation (M-QAM) signals which is based on amplitude histogram space of the incoming data after analog-to-digital conversion, chromatic dispersion com-pensation at the receiver. We demonstrated the identifica-tion of quadrature phase-shift keying (QPSK), 16-QAM, 64-QAM formats with an amplitude histogram space. Simulation results show that it achieve 100% identification accuracy when the incoming signal OSNR is 14 dB to identify the modulation format of QPSK, 16-QAM, and 64-QAM signals in digital coherent systems. The method has low complexity and small delay. 展开更多
关键词 modulation FORMAT identification (MFI) AMPLITUDE HISTOGRAM SPACE high-order modulation FORMAT optical performance monitoring
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Fast identification of digital amplitude modulation level at low signal-to-noise ratio
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作者 WEI Xiao-wei CAO Zhi-gang 《Frontiers of Electrical and Electronic Engineering in China》 CSCD 2006年第4期421-424,共4页
In order to rapidly and automatically identify the modulation level of digital amplitude modulated signals at low signal-to-noise ratio(SNR),a method of identifying the modulation levels of M-ary quadrature amplitude ... In order to rapidly and automatically identify the modulation level of digital amplitude modulated signals at low signal-to-noise ratio(SNR),a method of identifying the modulation levels of M-ary quadrature amplitude modulation(M-QAM)and M-ary amplitude shift keying(M-ASK)is proposed.In this method,wavelet transform with the optimal scale is used to identify the modulation levels of M-QAM and M-ASK signals.The performance of this method was investigated through simulations.Simulation results show that when the SNR is not lower than–4 dB,the percentage of correct identification of M-QAM is higher than 93%,and when the SNR is not lower than–10 dB,the percentage of correct identification of M-ASK is higher than 90%,using only 100 observed symbols.It shows that this method can rapidly acquire good performance at a low SNR. 展开更多
关键词 signal processing modulation identification wavelet transform
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基于改进轻量级深度卷积神经网络的果树叶片分类及病害识别模型设计 被引量:3
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作者 买买提·沙吾提 李荣鹏 +2 位作者 蔡和兵 赵明 梁嘉曦 《森林工程》 北大核心 2025年第2期277-287,共11页
新疆是中国重要的林果产业基地,特色林果业是区域经济发展的重要组成部分。为预防果树病害制约林果业发展,设计一款归一化注意力(normalization-based attention module,NAM)轻量级深度卷积神经网络(MobileNet-V2)果树叶片分类及病害识... 新疆是中国重要的林果产业基地,特色林果业是区域经济发展的重要组成部分。为预防果树病害制约林果业发展,设计一款归一化注意力(normalization-based attention module,NAM)轻量级深度卷积神经网络(MobileNet-V2)果树叶片分类及病害识别模型。其中融入轻量型的归一化注意力机制,提高模型对特征信息的敏感度,使模型关注显著性特征。同时,将L1正则化(L1 regularization或losso)添加到损失函数中,对权重进行稀疏性惩罚,抑制非显著性权重。试验结果表明,在叶片分类中,模型对自构建植物叶片病害识别数据集(Plant Village)、混合数据集的分类结果均表现良好,准确率分别达到97.05%、98.73%、94.91%,具有较好的泛化能力。在病害识别中,MobileNet-V2 NAM模型实现94.55%的识别准确率,高于深度卷积神经网络(AlexNet)、视觉几何群网络(VGG16)经典卷积神经网络(Convolutional Neural Networks,CNN)模型,且模型参数量只有3.56 M。MobileNet-V2 NAM在具有良好准确率同时保持了较低的模型参数量,为深度学习模型嵌入到移动设备提供技术支持。 展开更多
关键词 新疆 果树分类 病害识别 归一化注意力轻量级深度卷积神经网络(MobileNet-V2 NAM) 归一化注意力机制
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考虑电热耦合特性的电池模组多状态协同估计方法研究 被引量:1
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作者 颜宁 李吉洋 +2 位作者 李相俊 郑佳辉 王晓龙 《中国电机工程学报》 北大核心 2025年第16期6340-6353,I0017,共15页
针对电池电气特性与热特性之间复杂的耦合关系、温度对电池功率性能的影响以及荷电状态(state of charge,SOC)、温度状态(stateoftemperature,SOT)与峰值功率状态(state of power,SOP)之间的复杂关联等问题,该文提出一种考虑电热耦合特... 针对电池电气特性与热特性之间复杂的耦合关系、温度对电池功率性能的影响以及荷电状态(state of charge,SOC)、温度状态(stateoftemperature,SOT)与峰值功率状态(state of power,SOP)之间的复杂关联等问题,该文提出一种考虑电热耦合特性的电池模组多状态协同估计方法。首先,分析电池电气特性与热特性之间的耦合关系,将分数阶等效电路模型与集总参数双态热模型结合,构建电池模组电热耦合模型。其次,针对电热耦合关系需要准确的SOC与SOT来维持的问题,采用自适应扩展卡尔曼算法(adaptive extended Kalman filter,AEKF)实现电池模组SOC与SOT估计。最后,分析不同状态之间的关联特性,将电池的SOC、SOT引入到多约束条件下的峰值SOP估计中,实现电池模组多状态协同估计,提高电池状态估计的准确性。仿真结果表明,所提方法在SOC初始误差为20%情况下,能够快速收敛至真实值,且均方根误差在0.52%以内,核心温度与表面温度估计误差分别在0.36和0.31℃以内。在40℃时,核心温度约束起作用,峰值功率估计结果显著降低,为动力电池的实时安全监控提供了有力保障。 展开更多
关键词 电热耦合 多状态协同估计 自适应扩展卡尔曼算法
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一种具有低调制深度和低功耗的自适应抗噪超高频RFID解调器设计
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作者 王翊 陈冲 +1 位作者 许耀华 柏娜 《安徽大学学报(自然科学版)》 北大核心 2025年第1期61-69,共9页
超高频射频识别技术(radio frequency identification,简称RFID)是目前RFID发展的主流,但是传统的RFID幅度调制(amplitude shift keying,简称ASK)解调器在应对低调制深度的射频输入信号时难以实现精准解调.针对这种情况,该文基于GJB7377... 超高频射频识别技术(radio frequency identification,简称RFID)是目前RFID发展的主流,但是传统的RFID幅度调制(amplitude shift keying,简称ASK)解调器在应对低调制深度的射频输入信号时难以实现精准解调.针对这种情况,该文基于GJB7377.1B标准系统的超高频RFID ASK解调器,设计了一个由包络检测、低通滤波、放大器和比较器组成的低功耗、自适应抗噪ASK解调器.与传统的RFID ASK解调器相比,使用了迟滞放大器来实现低调制深度下的精准解调,使用了偏置电路来降低功耗,并使用了迟滞单元来抗噪.经过测试和验证,该RFID ASK解调器可以在2.31%的最小调制深度下解调信号,其功耗仅为421.63 nW,且在射频信号(radio frequency,简称RF)加入噪声的情况下也能实现精准解调. 展开更多
关键词 低调制深度 低功率 自适应抗噪 超高频射频识别技术
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基于多任务学习的通用滤波多载波调制识别与信噪比估计
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作者 张天骐 吴云戈 +1 位作者 吴仙越 李春运 《电讯技术》 北大核心 2025年第8期1213-1220,共8页
非协作通信通用滤波多载波(Universal Filtered Multi-carrier,UFMC)信号子载波所存在的调制识别以及信噪比估计问题有待解决,但目前研究只针对于单一任务。对此,提出一种利用多任务学习框架的神经网络模型,同时解决调制识别以及信噪比... 非协作通信通用滤波多载波(Universal Filtered Multi-carrier,UFMC)信号子载波所存在的调制识别以及信噪比估计问题有待解决,但目前研究只针对于单一任务。对此,提出一种利用多任务学习框架的神经网络模型,同时解决调制识别以及信噪比估计任务。首先得到UFMC系统接收端信号,求解出信号同相正交分量作为输入特征;接着在多任务学习框架上构建神经网络,采用的神经网络是将卷积神经网络与长短时记忆网络串联;最后利用上述模型对两个任务进行联合求解。实验结果表明,所构建多任务学习模型性能优于单任务学习,在信噪比为0 dB时,子载波调制识别准确率提升7.71%,信噪比估计均方误差减小45.6%。 展开更多
关键词 通用滤波多载波(UFMC) 调制识别 信噪比估计 多任务学习 神经网络
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基于无意调相边带信息的雷达辐射源个体识别
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作者 黄湘松 王振 +1 位作者 潘大鹏 赵一洋 《电子与信息学报》 北大核心 2025年第6期1762-1771,共10页
无意调相是雷达辐射源个体识别中的关键信息,能够提供细微的相位变化信息,捕捉到不同辐射源的微小差异,在区分具有相似硬件结构的雷达辐射源时具有显著优势。针对同一厂家生产的同型号辐射源无意调相特性区分性不明显的问题,该文提出一... 无意调相是雷达辐射源个体识别中的关键信息,能够提供细微的相位变化信息,捕捉到不同辐射源的微小差异,在区分具有相似硬件结构的雷达辐射源时具有显著优势。针对同一厂家生产的同型号辐射源无意调相特性区分性不明显的问题,该文提出一种基于无意调相边带信息与深度学习相结合的个体识别方法。通过深入挖掘无意调相特性中的边带信息,增强不同辐射源个体间的差异性,并引入双路循环膨胀卷积网络增加神经网络感受野。实验实测数据显示,该方法在信噪比为5 dB的条件下,仍能对10台同型号的辐射源实现87.58%的平均识别准确率,对比1维残差网络,识别精度提高了21.41%。 展开更多
关键词 辐射源个体识别 无意调相 边带信息 循环膨胀卷积网络 同步压缩小波变换
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