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Wave-Number Spectral Characteristics of Drift Wave Micro-Turbulence with Large-Scale Structures
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作者 李继全 Y.KISHIMOTO 《Plasma Science and Technology》 SCIE EI CAS CSCD 2011年第3期297-301,共5页
Wave-number spectral characteristics of drift wave micro-turbulence with large-scale structures (LSSs) including zonal flows (ZFs) and Kelvin-Holmheltz (KH) mode are investigated based on three dimensional gyrof... Wave-number spectral characteristics of drift wave micro-turbulence with large-scale structures (LSSs) including zonal flows (ZFs) and Kelvin-Holmheltz (KH) mode are investigated based on three dimensional gyrofluid simulations in a slab geometry. The focus is on the property of the wave-number spectral scaling law of the ambient turbulence under the back reaction of the self-generated LSSs. A comparison of the spectral scaling laws between ion/electron temperature gradient (ITG/ETG) driven turbulences is presented. It is shown that the spectral scaling of the ITG turbulence with robust ZFs is fitted well by an exponential-law function (Φ^2/2)E∝e^-λkx in kx and a power-law one in (Φ^2/2)p∝ky^-β in ky. However, the ETG turbulence is characterized by a mixing Kolmogorov-like power-law and exponential-law (Φ^2/2)E∝e-λkx'yk^-3x,y/(1 + k^2x,y)^2 scaling for both kx and ky spectra due to the ZFs and KH mode dynamics, with λ and β the slope index factors. The underlying physical mechanism is understood as the spectral scattering caused by the back-reaction of the LSSs on the ambient turbulence. These findings may provide helpful guideline to diagnose the plasma fluctuations and flow structures in experiments. 展开更多
关键词 spectral scaling law zonal flows micro-turbulence gyrofluid simulation
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Spectral matching algorithm based on nonsubsampled contourlet transform and scale-invariant feature transform 被引量:4
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作者 Dong Liang Pu Yan +2 位作者 Ming Zhu Yizheng Fan Kui Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第3期453-459,共7页
A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low freq... A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix (or matching result) reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy. 展开更多
关键词 point pattern matching nonsubsampled contourlet transform scale-invariant feature transform spectral algorithm.
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Single-Channel Speech Enhancement Using Critical-Band Rate Scale Based Improved Multi-Band Spectral Subtraction 被引量:1
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作者 Navneet Upadhyay Abhijit Karmakar 《Journal of Signal and Information Processing》 2013年第3期314-326,共13页
This paper addresses the problem of single-channel speech enhancement in the adverse environment. The critical-band rate scale based on improved multi-band spectral subtraction is investigated in this study for enhanc... This paper addresses the problem of single-channel speech enhancement in the adverse environment. The critical-band rate scale based on improved multi-band spectral subtraction is investigated in this study for enhancement of single-channel speech. In this work, the whole speech spectrum is divided into different non-uniformly spaced frequency bands in accordance with the critical-band rate scale of the psycho-acoustic model and the spectral over-subtraction is carried-out separately in each band. In addition, for the estimation of the noise from each band, the adaptive noise estimation approach is used and does not require explicit speech silence detection. The noise is estimated and updated by adaptively smoothing the noisy signal power in each band. The smoothing parameter is controlled by a-posteriori signal-to-noise ratio (SNR). For the performance analysis of the proposed algorithm, the objective measures, such as, SNR, segmental SNR, and perceptual evaluations of the speech quality are conducted for the variety of noises at different levels of SNRs. The speech spectrogram and objective evaluations of the proposed algorithm are compared with other standard speech enhancement algorithms and proved that the musical structure of the remnant noise and background noise is better suppressed by the proposed algorithm. 展开更多
关键词 SINGLE-CHANNEL SPEECH Enhancement Critical-Band RATE scale spectral Over-Subtraction Adaptive Noise Estimation Objective Measure SPEECH Spectrograms
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Seasonal Characteristics and Interannual Variability of Monthly Scale Low-Frequency Oscillation in a Low-Order Global Spectral Model
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作者 倪允琪 张勤 林武银 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 1991年第3期307-316,共10页
Analysis is done of five-year low-pass filtered data by a five-layer low-order global spectral model, indicating that although any non-seasonal external forcing is not considered in the model atmosphere,monthly-scale ... Analysis is done of five-year low-pass filtered data by a five-layer low-order global spectral model, indicating that although any non-seasonal external forcing is not considered in the model atmosphere,monthly-scale anomaly takes place which is of remarkable seasonality and interannual variability.Analysis also shows that for the same seasonal external forcing the model atmosphere can exhibit two climatic states,similar in the departure pattern but opposite in sign, indicating that the anomaly is but the manifestation of the adverse states, which supports the theory of multi-equilibria proposed by Charney and Devore(1979) once again.Finally, the source for the low-frequency oscillation of the global atmosphere is found to be the convective heat source / sink inside the tropical atmosphere as discussed before in our study.Therefore, the key approach to the exploration of atmospheric steady low-frequency oscillation and the associated climatic effect lies in the examination of the distribution of convective heat sources / sinks and the variation in the tropical atmosphere. 展开更多
关键词 Seasonal Characteristics and Interannual Variability of Monthly scale Low-Frequency Oscillation in a Low-Order Global spectral Model
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核心图构造驱动的大规模高光谱图像高效聚类方法
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作者 冯晓凤 杨易扬 +1 位作者 杨戈平 巩志国 《计算机工程与应用》 北大核心 2026年第6期279-292,共14页
大规模高光谱图像(hyperspectral image,HSI)聚类因其像素数量庞大、光谱波段丰富,面临计算复杂度和可扩展性上的重大挑战。为解决这一问题,提出了一种核心图(core graph,CG)构建方法,通过选择一组核心点代表原始高光谱图像的像素,构建... 大规模高光谱图像(hyperspectral image,HSI)聚类因其像素数量庞大、光谱波段丰富,面临计算复杂度和可扩展性上的重大挑战。为解决这一问题,提出了一种核心图(core graph,CG)构建方法,通过选择一组核心点代表原始高光谱图像的像素,构建核心图以有效捕捉原始高光谱图像数据的全局和局部空间结构,同时显著降低非线性流形学习的复杂性,从而减少内存需求并提升计算效率。该方法具有算法无关性,能够灵活嵌入不同的聚类框架中。结合谱聚类(spectral clustering,SC)和密度峰值聚类(density peak clustering,DPC),分别提出了核心图驱动的谱聚类算法(core graph-based spectral clustering,CGSC)和核心图驱动的密度峰值聚类算法(core graph-based density peak clustering,CGDPC)。实验结果表明,核心图驱动的聚类算法在多个HSI数据集上展现了卓越的计算效率和聚类性能,适用于大规模高光谱图像的聚类任务。 展开更多
关键词 核心图 大规模 高光谱图像 谱聚类 密度峰值聚类
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4-Scale几何光学模型冠层反射率模拟的空间尺度适用性 被引量:3
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作者 魏萌 范文义 +3 位作者 张海军 于颖 吴国明 程腾辉 《应用生态学报》 CAS CSCD 北大核心 2023年第3期605-613,共9页
明确4-Scale模型模拟森林冠层反射率适用的空间尺度,有助于提高其应用于不同植被类型冠层反射率模拟时的精度,进而提升其开展叶面积指数、郁闭度和其他参数的反演精度。以黑龙江省尚志市帽儿山实验林场2块100 m×100 m森林样地(阔... 明确4-Scale模型模拟森林冠层反射率适用的空间尺度,有助于提高其应用于不同植被类型冠层反射率模拟时的精度,进而提升其开展叶面积指数、郁闭度和其他参数的反演精度。以黑龙江省尚志市帽儿山实验林场2块100 m×100 m森林样地(阔叶林与混交林各一块)为研究对象,分别分割为10、20、30、40和50 m空间尺度,使用4-Scale模型模拟森林冠层反射率,采用局部平均法、最邻近法、双线性内插法和立方卷积法对空间分辨率为10 m的Sentinel-2影像升尺度转换至其他尺度并评价,对比分析模拟冠层反射率和遥感像元反射率,明确混交林和阔叶林适合4-Scale模型高精度反演参数的空间尺度。结果表明:4-Scale模型整体低估了像元森林冠层反射率,混交林和阔叶林冠层反射率在20 m尺度的模拟效果均最差,红光波段和近红外波段的均方根误差(RMSE)和平均绝对偏差(MAE)均较大;>20 m尺度的模拟效果开始变好,混交林40 m、阔叶林30 m时模型的适用性最佳,红光波段和近红外波段下,模拟值与遥感像元反射率之差的均值和标准差最小,RMSE和MAE同样最小;10 m尺度混交林和阔叶林模拟结果均不稳定,均值与标准差的规律不一致,相同波段下的RMSE和MAE差距较大。 展开更多
关键词 4-scale模型 森林冠层反射率 尺度效应 光谱响应函数 尺度转换
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Study on Multi-Scale Blending Initial Condition Perturbations for a Regional Ensemble Prediction System 被引量:40
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作者 ZHANG Hanbin CHEN Jing +2 位作者 ZHI Xiefei WANG Yi WANG Yanan 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2015年第8期1143-1155,共13页
An initial conditions (ICs) perturbation method was developed with the aim to improve an operational regional ensemble prediction system (REPS). Three issues were identified and investigated: (1) the impacts of... An initial conditions (ICs) perturbation method was developed with the aim to improve an operational regional ensemble prediction system (REPS). Three issues were identified and investigated: (1) the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; (2) the scale characteristic of the IC perturbations of the REPS; and (3) whether the REPS's skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system (GEPS) were analyzed. A "multi-scale blending" (MSB) IC perturbation scheme was developed, and the main findings can be summarized as follows: The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification. 展开更多
关键词 regional ensemble prediction system spectral analysis multi-scale blending initial condition perturbations
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Prediction of Vibration Characteristics in Beam Structure Using Sub-Scale Modeling with Experimental Validation 被引量:1
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作者 ZAI Behzad Ahmed SAMI Saad +2 位作者 KHAN M Amir AHMAD Furqan PARK Myung Kyun 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2015年第5期928-934,共7页
Geometric or sub-scale modeling techniques are used for the evaluation of large and complex dynamic structures to ensure accurate reproduction of load path and thus leading to true dynamic characteristics of such stru... Geometric or sub-scale modeling techniques are used for the evaluation of large and complex dynamic structures to ensure accurate reproduction of load path and thus leading to true dynamic characteristics of such structures. The sub-scale modeling technique is very effective in the prediction of vibration characteristics of original large structure when the experimental testing is not feasible due to the absence of a large testing facility. Previous researches were more focused on free and harmonic vibration case with little or no consideration for readily encountered random vibration. A sub-scale modeling technique is proposed for estimating the vibration characteristics of any large scale structure such as Launch vehicles, Mega structures, etc., under various vibration load cases by utilizing precise scaled-down model of that dynamic structure. In order to establish an analytical correlation between the original structure and its scaled models, different scale models of isotropic cantilever beam are selected and analyzed under various vibration conditions( i.e. free, harmonic and random) using finite element package ANSYS. The developed correlations are also validated through experimental testing The prediction made from the vibratory response of the scaled-down beam through the established sets of correlation are found similar to the response measured from the testing of original beam structure. The established correlations are equally applicable in the prediction of dynamic characteristics of any complex structure through its scaled-down models. This paper presents modified sub-scale modeling technique that enables accurate prediction of vibration characteristics of large and complex structure under not only sinusoidal but also for random vibrations. 展开更多
关键词 sub-scale modeling resonance frequency vibration characteristics scale factors power spectral density
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Scaling of weighted spectral distribution in weighted small-world networks
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作者 Bo Jiao Xiao-Qun Wu 《Chinese Physics B》 SCIE EI CAS CSCD 2017年第2期536-545,共10页
Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution(W SD) have focused on unweighted ... Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution(W SD) have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the W SD in a deterministic weighted scale-free small-world network model and find that the W SD grows sublinearly with increasing network order(i.e., the number of nodes) and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the W SD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents. 展开更多
关键词 weighted spectral distribution weighted small-world network scaling
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二维随机裂缝介质横波散射衰减数值研究 被引量:1
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作者 周浩 符力耘 +2 位作者 曹辉 俞军 邓继新 《地球物理学报》 北大核心 2025年第2期668-679,共12页
声波衰减对裂缝识别更为敏感,因此在非常规油气勘探和压裂监测等领域有着广泛的应用前景.裂缝型油气储层非均质性强,散射效应显著,但长波长假设下的等效介质理论无法准确描述散射导致的声波衰减.本研究利用交错网格有限差分方法,在二维... 声波衰减对裂缝识别更为敏感,因此在非常规油气勘探和压裂监测等领域有着广泛的应用前景.裂缝型油气储层非均质性强,散射效应显著,但长波长假设下的等效介质理论无法准确描述散射导致的声波衰减.本研究利用交错网格有限差分方法,在二维随机裂缝介质上模拟了标量横波(SH波)的传播,并研究了裂缝尺度、密度以及交叉对横波散射衰减的影响.研究发现,裂缝长度l_(c)、裂缝密度γ和背景介质波数k_(0)可定量表征散射衰减.裂缝长度l_(c)小于背景介质波长λ_(0)的1/30时,可以忽略散射衰减;当k_(0)l_(c)/2<1时,衰减随着k_(0)l_(c)/2的增大而增大,反之,衰减随着k_(0)l_(c)/2的增大而减小;当l_(c)≈λ_(0)/3时,衰减最强.裂缝交叉会加强k_(0)l_(c)/2<1时的散射衰减,而减弱k_(0)l_(c)/2>1时的衰减.这种定量关系有助于理解多尺度裂缝的横波散射衰减特征,对声波测井和勘探地震中的裂缝识别问题具有实用价值. 展开更多
关键词 声波衰减 裂缝识别 裂缝散射 谱比法 多尺度裂缝
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Time-Spectral Solution of Initial-Value Problems—Subdomain Approach
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作者 Jan Scheffel Ahmed A. Mirza 《American Journal of Computational Mathematics》 2012年第2期72-81,共10页
Temporal and spatial subdomain techniques are proposed for a time-spectral method for solution of initial-value problems. The spectral method, called the generalised weighted residual method (GWRM), is a generalisatio... Temporal and spatial subdomain techniques are proposed for a time-spectral method for solution of initial-value problems. The spectral method, called the generalised weighted residual method (GWRM), is a generalisation of weighted residual methods to the time and parameter domains [1]. A semi-analytical Chebyshev polynomial ansatz is employed, and the problem reduces to determine the coefficients of the ansatz from linear or nonlinear algebraic systems of equations. In order to avoid large memory storage and computational cost, it is preferable to subdivide the temporal and spatial domains into subdomains. Methods and examples of this article demonstrate how this can be achieved. 展开更多
关键词 Initial-Value Problem Multiple TIME scales Time-spectral spectral METHOD WEIGHTED RESIDUAL METHOD Subdomains Domain Decomposition
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Stability of weighted spectral distribution in a pseudo tree-like network model
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作者 焦波 聂原平 +4 位作者 黄赪东 杜静 郭荣华 黄飞 石建迈 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第5期479-486,共8页
The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distri... The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution(i.e., a spectral graph feature) as the network order increases. First, we use deterministic scale-free networks generated by a pseudo treelike model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system. 展开更多
关键词 weighted spectral distribution pseudo tree-like model deterministic network scale-free and small-world network
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基于多尺度空间-光谱特征提取的颜料高光谱图像分类方法
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作者 汤斌 罗希玲 +6 位作者 王建旭 范文奇 孙玉宇 刘家路 唐欢 赵雅 钟年丙 《光谱学与光谱分析》 北大核心 2025年第8期2364-2372,共9页
颜料不仅赋予文物色彩和美感,更承载着丰富的历史、文化与技术信息,因此对颜料的准确分类与识别是古代彩绘作品修复、保护及学术研究的重要基础。通过检测颜料的种类与化学成分,不仅能帮助确定作品的创作年代、地域特征及工艺风格,还能... 颜料不仅赋予文物色彩和美感,更承载着丰富的历史、文化与技术信息,因此对颜料的准确分类与识别是古代彩绘作品修复、保护及学术研究的重要基础。通过检测颜料的种类与化学成分,不仅能帮助确定作品的创作年代、地域特征及工艺风格,还能为科学修复提供指导依据。然而,传统颜料分析受限于样品尺寸、表面平整度,且部分分析方法需要取样,对文物造成不可逆损伤,这使得古书画颜料的检测面临诸多挑战。高光谱成像技术(HSI)凭借其无损检测、广域扫描及获取完整光谱信息的优势,成为文物颜料分析的重要工具。HSI克服了样品表面不平整、尺寸受限等问题,能够从不同波段获取细致的光谱和空间信息,帮助提取颜料的微观特征。旨在利用HSI技术实现古书画颜料的精准分类与深度特征提取,以应对复杂场景下的颜料检测挑战。为此,我们提出了一种多尺度空间-光谱特征融合的方法,在分析过程中结合不同层次的信息:利用光谱-空间注意力机制捕捉细节特征,并通过视觉转换器(ViT)模型获取图像整体的高层语义信息,从而增强对复杂颜料特征的表示能力和分类性能。实验结果表明,该方法在模拟画作样品上的分类性能显著优于传统和其他深度学习模型:与支持向量机(SVM)相比,分类精度提升了34.35%;相较于HyBridSN与SSRN模型,精度分别提高了8.93%和5.6%。本方法不仅提升了颜料检测的准确性,还为古书画的科学修复和价值保护提供了无损、可靠的技术支持,并为文物保护的智能化发展奠定了技术基础。 展开更多
关键词 高光谱成像 多尺度特征融合 Vision Transformer 光谱-空间注意力 颜料分类
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基于混合光谱增强与多尺度空间聚合的高光谱图像分类方法
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作者 欧阳宁 黄辰钰 林乐平 《吉林大学学报(工学版)》 北大核心 2025年第11期3727-3735,共9页
由于高光谱图像存在同物异谱和异物同谱现象,仅依赖光谱信息无法充分表征高光谱图像的特征,因此可引入空间信息以更准确地捕捉物体特征。为此,本文提出一种基于混合光谱增强与多尺度空间聚合的高光谱图像分类方法。该方法设计了混合光... 由于高光谱图像存在同物异谱和异物同谱现象,仅依赖光谱信息无法充分表征高光谱图像的特征,因此可引入空间信息以更准确地捕捉物体特征。为此,本文提出一种基于混合光谱增强与多尺度空间聚合的高光谱图像分类方法。该方法设计了混合光谱增强模块,利用小波变换构建光谱的多尺度局部特征,通过Transformer架构生成光谱的全局特征,以增强光谱特征的类内一致性。同时,设计了多尺度空间聚合模块,用于提取空间特征固有的多尺度信息,并建立不同尺度间的交互关系,以生成更具鲁棒性的土地覆盖表示,从而进一步提升分类性能。实验结果表明:本文方法相较于其他先进网络表现出显著的优越性,能有效获取更丰富的光谱信息和空间特征表示。 展开更多
关键词 高光谱图像分类 混合光谱增强模块 小波变换 多尺度空间聚合模块
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平面声波扰动大气湍流非柯尔莫哥洛夫谱折射率功率谱分布
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作者 王明军 刘帅 +2 位作者 吴小虎 席建霞 张佳琳 《计算物理》 北大核心 2025年第4期500-510,共11页
本文基于声波能量和湍流能量平衡方程,推导在平面声波扰动下各向同性和各向异性Non-Kolmogoro(非柯尔莫哥洛夫谱)折射率功率谱函数的表达式,数值仿真在不同声源功率和频率下,平面声源激发产生的声场能量分布。计算声源参数一定时,不同... 本文基于声波能量和湍流能量平衡方程,推导在平面声波扰动下各向同性和各向异性Non-Kolmogoro(非柯尔莫哥洛夫谱)折射率功率谱函数的表达式,数值仿真在不同声源功率和频率下,平面声源激发产生的声场能量分布。计算声源参数一定时,不同功率谱幂律和各向异性因子下的Non-Kolmogorov折射率功率谱函数的分布情况。结果表明:在声波传输距离一定时,各向同性Non-Kolmogorov折射率功率谱随功率谱幂律的增大呈整体下降趋势;各向异性Non-Kolmogorov折射率功率谱随各向异性因子的增大呈整体上升状态;在空间波数一定时,Non-Kolmogorov折射率功率谱随声波传输距离的增大呈现极大值和极小值交替变化。 展开更多
关键词 平面声波 声场能量 大气湍流 湍涡尺度 Non-Kolmogorov谱模型
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冬小麦叶片SPAD遥感探测的光谱尺度效应 被引量:1
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作者 池浩然 李映雪 +1 位作者 吴芳 邹晓晨 《农业工程学报》 北大核心 2025年第2期196-205,共10页
叶片SPAD(soil and plant analyzer development)值表征了叶片叶绿素相对含量,是监测农作物长势和营养状况的重要参数。光学遥感是大面积无损探测叶片SPAD值的重要手段。然而,由于不同光谱尺度数据探测光谱变化存在差异,影响了光学探测... 叶片SPAD(soil and plant analyzer development)值表征了叶片叶绿素相对含量,是监测农作物长势和营养状况的重要参数。光学遥感是大面积无损探测叶片SPAD值的重要手段。然而,由于不同光谱尺度数据探测光谱变化存在差异,影响了光学探测作物生化参数的精度,但目前很少有研究系统评估不同光谱尺度对探测冬小麦叶片SPAD值的影响。为优化光谱尺度提升叶片SPAD探测精度,该研究通过连续4年田间试验,获取冬小麦4个关键生育期(拔节期、抽穗期、开花期和灌浆期)和3种施氮水平(N1、N2和N3)条件下的冠层光谱反射率和叶片SPAD值,评估了5种光谱尺度(1、5、10、25和50 nm)下单一波段反射率和植被指数对叶片SPAD值敏感性差异及对机器学习模型估算SPAD值的影响。结果表明,红光波段反射率对SPAD值敏感性最大,光谱尺度敏感性变异系数Var为0.497。红边波段波长710 nm反射率受到光谱尺度影响最大,在全生育期敏感性变异系数Var为1.000。全生育期敏感性最佳植被指数为m ND705,在50 nm光谱尺度对SPAD的敏感性最高(R^(2)=0.685)且光谱尺度敏感性变异系数低(Var=0.014)。在4个单一生育期中,mND705在灌浆期对SPAD的敏感性最佳(R^(2)=0.895)且受到光谱尺度的影响小(Var=0.014)。施氮水平的增加提升了植被指数对SPAD的敏感性。优化光谱尺度提升了机器学习模型估算SPAD的能力,全生育期中以25 nm光谱尺度构建的偏最小二乘回归模型对SPAD的估算精度最佳(R^(2)=0.816和均方根误差RMSE=4.04)。该研究为从优化光谱尺度角度优化光学传感器选择和设计、光谱植被指数波段选择和机器学习模型光谱特征构建提供了理论基础。 展开更多
关键词 光谱尺度 植被指数 叶绿素含量 冬小麦 机器学习
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基于空间增强自注意力网络的无监督全色锐化方法
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作者 熊璋玺 李伟 +1 位作者 杨飞 林弘杨 《中国空间科学技术(中英文)》 北大核心 2025年第4期48-60,共13页
针对全色图像与多光谱图像融合时存在空间纹理不丰富、光谱失真等问题,提出一种基于空间增强自注意力网络(Transformer)的无监督全色锐化方法。首先,设计一种多尺度特征提取模块获取全色图像与多光谱图像不同尺度下的特征信息,从而提高... 针对全色图像与多光谱图像融合时存在空间纹理不丰富、光谱失真等问题,提出一种基于空间增强自注意力网络(Transformer)的无监督全色锐化方法。首先,设计一种多尺度特征提取模块获取全色图像与多光谱图像不同尺度下的特征信息,从而提高特征的泛化能力与模型的鲁棒性。其次,设计高频信息提取模块来提取全色图像的高频信息。获取的全色图像与多光谱图像的多尺度特征在经过简单融合后与全色图像的高频信息一同输入设计的空间增强Transformer中,设计的空间增强Transformer由自注意力机制与空间纹理增强注意力机制组成,自注意力机制可以捕获自相似性并提取长距离特征,空间纹理增强注意力机制确保只对纹理、边缘以及细节部分做增强。最后,特征经过多层空间增强Transformer融合与增强后重建得到具有高空间分辨率的多光谱图像。在PanCollection数据集里的GF-2和WV-3数据上分别进行对比实验,并使用7种质量评价指标对各方法的融合图像进行客观质量评价,提出方法的融合图像在两种数据集上的质量评价指标QNR均表现最优,分别为0.9692与0.9327。融合图像的视觉效果与质量评价指标表明提出的方法在主观视觉上和客观评价上均优于对比方法,能有效降低融合图像的空谱失真度。 展开更多
关键词 全色锐化 全色图像 多光谱图像 多尺度特征提取 自注意力网络
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基于自适应融合全局和局部信息的锚点多视图聚类
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作者 冉戆 王思为 祝恩 《郑州大学学报(理学版)》 北大核心 2025年第4期30-39,共10页
基于子空间的多视图聚类算法因其良好的聚类性能和数学可解释性而备受关注。其中,一些基于锚点策略的大规模多视图子空间聚类算法,能够有效降低算法的时空复杂度。然而,现有的算法往往从全局结构中学习子空间自表示矩阵,忽视了视图数据... 基于子空间的多视图聚类算法因其良好的聚类性能和数学可解释性而备受关注。其中,一些基于锚点策略的大规模多视图子空间聚类算法,能够有效降低算法的时空复杂度。然而,现有的算法往往从全局结构中学习子空间自表示矩阵,忽视了视图数据、锚点和子空间自表示矩阵之间的局部结构信息。受多视图自加权多图学习算法的启发,提出了基于自适应融合全局和局部信息的锚点多视图聚类(AMVC-AFGL)算法。所提算法旨在通过自适应分配视图权重,融合数据之间的全局信息和局部信息,为每个视图数据学习一个更有效的子空间锚图矩阵,进而拼接为较小的融合锚图矩阵然后进行谱聚类。在公开的10个真实基准数据集上开展了充分的实验,结果表明,与其他12个先进的多视图聚类算法相比,所提算法具有有效性和可扩展性。 展开更多
关键词 多视图聚类 自加权 锚点 子空间聚类 谱聚类 大规模
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基于时频双域特征融合与动态交互机制的短期电力负荷预测
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作者 王东风 张浩 +2 位作者 胡怡然 崔玉雷 黄宇 《电力科学与工程》 2025年第12期57-64,共8页
针对电力负荷序列时序动态性、多尺度特征及复杂周期规律给预测带来的难题,提出一种基于时频双域特征融合与动态交互机制的短期电力负荷预测方法,其核心架构为双谱网。首先,针对短期电力负荷数据的非平稳和非线性特性,采用基于阿尔法进... 针对电力负荷序列时序动态性、多尺度特征及复杂周期规律给预测带来的难题,提出一种基于时频双域特征融合与动态交互机制的短期电力负荷预测方法,其核心架构为双谱网。首先,针对短期电力负荷数据的非平稳和非线性特性,采用基于阿尔法进化算法改进的变分模态分解算法对负荷数据分解,得到若干本征模态函数;其次,设计频域特征增强机制,通过频谱注意力动态融合振幅谱与相位谱,并构建时频交叉注意力网络嵌入频域先验,结合跨维度门控实现特征校准;最后,基于多尺度金字塔解码器自适应融合时空特征生成预测值。以某市电力负荷数据集进行验证并与主流模型进行对比,结果表明所采用的预测方法具有更好的预测性能。 展开更多
关键词 时频双域 动态交互 双谱网 频域特征增强 多尺度金字塔解码器
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基于物理约束神经网络的单模光纤非线性效应高精度解析
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作者 祝沐 佟首峰 +1 位作者 丁蕴丰 张鹏 《物理学报》 北大核心 2025年第20期273-282,共10页
针对单模光纤中四波混频-受激拉曼散射(FWM-SRS)强非线性耦合效应难以解析的问题,本文提出了一种融合物理机理与神经网络的多尺度物理约束网络(MSPC-Net).该模型通过将非线性薛定谔方程(NLSE)的频域残差作为物理约束项嵌入网络优化过程... 针对单模光纤中四波混频-受激拉曼散射(FWM-SRS)强非线性耦合效应难以解析的问题,本文提出了一种融合物理机理与神经网络的多尺度物理约束网络(MSPC-Net).该模型通过将非线性薛定谔方程(NLSE)的频域残差作为物理约束项嵌入网络优化过程,并设计多尺度空洞卷积模块融合局部细节、中程展宽及长程衰减特征,实现了光谱成分分离与物理参数的联合高精度反演.在250 m与500 m单模石英光纤实验中,MSPC-Net重建斯托克斯光谱的均方根误差(RMSE)分别低至0.014与0.0173,较传统卷积神经网络降低超68%;其频率偏移预测的平均绝对误差分别为0.03 nm和0.04 nm,精度较现有方法提升约90%.在信噪比(SNR)为6 dB的噪声环境下,MSPC-Net对FWM次峰信息的检测正确率高达95.3%,伪峰率低于4.7%.模型得益于物理约束的引导及轻量化结构设计,在SNR=15 dB噪声下RMSE增幅仅9.8%,并具备良好的实时处理能力,可部署于嵌入式设备,为高功率光通信系统优化与分布式光纤传感提供高效解决方案.本研究通过将严格物理规律与多尺度特征提取相结合,有效解决了长距离光纤复杂非线性效应的解析难题,显著提升了预测结果的理论符合度与噪声鲁棒性. 展开更多
关键词 非线性光学 物理约束神经网络 多尺度特征提取 光谱分离
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