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A general n-th order spectral transform
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作者 Z. R. Bhatti (Department of Mathematics, Govt. Collage of Science Wahdat Road, Labors-54570, Pakistan) I. R. Durrani (Centre of Excellence in Soli. State Physics, University of the Punjab Labore-54590, Pakistan) S. Asghar (Department of Mathematics, Quaid 《Chinese Journal of Acoustics》 2001年第2期184-192,共9页
A general n-th order spectral transform and a technique for inverting this transform is described in this paper and the usefulness of the whole procedure is illustrated by the solution of a system of nonlinear Klein G... A general n-th order spectral transform and a technique for inverting this transform is described in this paper and the usefulness of the whole procedure is illustrated by the solution of a system of nonlinear Klein Gordon equations. 展开更多
关键词 A general n-th order spectral transform RE REAL
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Spectral transformation of constant mean curvature surfaces in H^3 and Weierstrass representation 被引量:1
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作者 陈卿 程艺 《Science China Mathematics》 SCIE 2002年第8期1066-1075,共10页
By using the method of integrable system, we study the deformation of constant mean curvature surfaces in three-dimensional hyperbolic space form H3. We also obtain a Weierstrass representation formula of the constant... By using the method of integrable system, we study the deformation of constant mean curvature surfaces in three-dimensional hyperbolic space form H3. We also obtain a Weierstrass representation formula of the constant mean curvature surfaces with mean curvature greater than 1. 展开更多
关键词 HYPERBOLIC space mean curvature spectral transformation WEIERSTRASS representation formula.
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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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三维卷积与Transformer支持下联合空谱特征的高光谱影像分类 被引量:1
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作者 何光 吴田军 《计算机工程与应用》 北大核心 2025年第2期259-272,共14页
由于CNN对局部特征提取能力强,目前仍是高光谱影像处理和分析中的主流深度模型,但是CNN感受野有限,无法建立长距离依赖关系,学习全局语义信息受限。Transformer的自注意力机制可以对输入序列中的每个位置进行注意力计算,从而能有效获取... 由于CNN对局部特征提取能力强,目前仍是高光谱影像处理和分析中的主流深度模型,但是CNN感受野有限,无法建立长距离依赖关系,学习全局语义信息受限。Transformer的自注意力机制可以对输入序列中的每个位置进行注意力计算,从而能有效获取全局上下文信息。如何实现CNN和Transformer的技术耦合并充分利用空间信息和光谱信息进行高光谱遥感影像分类是一个重要的待研问题。鉴于此,提出一种新的基于三维卷积和Transformer的高光谱遥感影像分类方法,尝试联合空谱特征实现解译能力的提升。使用主成分分析方法对高光谱遥感影像沿垂直方向降维;用非负矩阵分解算法对降维后遥感影像沿水平方向进行空间特征提取,将两种工具处理后遥感影像进行拼接,以充分保留信息;再用三维卷积核对拼接后遥感影像进行空间特征和光谱特征的综合提取;用Transformer的注意力机制对提取空间信息和光谱信息的遥感影像序列建立长距离依赖关系并使用多层感知机完成分类任务。实验表明,所提方法在WHU-Hi龙口、汉川、洪湖以及雄安新区马蹄湾村数据集上均表现出比对比方法更优异的分类性能,表明该方法具有一定的泛化性和稳健性。 展开更多
关键词 非负矩阵分解 特征融合 三维卷积 空谱联合 transformER 高光谱遥感影像分类
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A Short Note on a Differential-Difference Gauge Transformation and a New Spectral Problem
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作者 陈奎 张大军 《Chinese Physics Letters》 SCIE CAS CSCD 2016年第10期1-2,共2页
We show that a class of spectral problems are related to the spectral problem of the Volterra lattice through a gauge transformation. The transformation is given. We hope that our discussion can draw attention to the ... We show that a class of spectral problems are related to the spectral problem of the Volterra lattice through a gauge transformation. The transformation is given. We hope that our discussion can draw attention to the study of gauge transformation theory of differential-difference integrable systems. 展开更多
关键词 of or in WELL that is A Short Note on a Differential-Difference Gauge transformation and a New spectral Problem been
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A SPECTRAL ESTIMATION ALGORITHM USING THE HOUSEHOLDER TRANSFORM
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作者 余辉里 《Journal of Electronics(China)》 1991年第1期77-85,共9页
Householder transform is used to triangularize the data matrix, which is basedon the near prediction error equation. It is proved that the sum of squared residuals for eachAR order can be obtained by the main diagonal... Householder transform is used to triangularize the data matrix, which is basedon the near prediction error equation. It is proved that the sum of squared residuals for eachAR order can be obtained by the main diagonal elements of upper triangular matrix, so thecolumn by column procedure can be used to develop a recursive algorithm for AR modeling andspectral estimation. In most cases, the present algorithm yields the same results as the covariancemethod or modified covariance method does. But in some special cases where the numerical ill-conditioned problems are so serious that the covariance method and modified covariance methodfail to estimate AR spectrum, the presented algorithm still tends to keep good performance. Thetypical computational results are presented finally. 展开更多
关键词 AR spectral estimation Householder transform AR PARAMETER RECURSIVE ALGORITHM
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Multi-spectral remote sensing image enhancement method based on PCA and IHS transformations 被引量:9
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作者 Shan-long LU Le-jun ZOU +2 位作者 Xiao-hua SHEN Wen-yuan WU Wei ZHANG 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2011年第6期453-460,共8页
This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) transformations.The PCA and the IHS trans... This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) transformations.The PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component,respectively.The enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation,and undertaking the inverse IHS transformation.The objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral image.On the basis of the visual and statistical analysis results of the experimental study,we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color distortion.It has potential advantages in image mapping optimization,object recognition,and weak information sharpening. 展开更多
关键词 Remote sensing Principal component analysis(PCA) Intensity-hue-saturation(IHS) transformation Image enhancement Spatial information spectral information
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Acoustic Measurement and Modeling of the Traditional Chinese Instrument Guzheng in Digital Transformation: A Case Study of Spectral and Resonance Analysis of Standard Pitch A440
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作者 Ning Li Dandan Li 《Open Journal of Acoustics》 2023年第2期17-30,共14页
This paper aims to explore the acoustic measurement and modeling of the traditional Chinese instrument, the guzheng, in the context of digital transformation, focusing on the spectral and resonance analysis of the sta... This paper aims to explore the acoustic measurement and modeling of the traditional Chinese instrument, the guzheng, in the context of digital transformation, focusing on the spectral and resonance analysis of the standard pitch A440. By employing various tools to conduct detailed analyses of the frequency response and resonance characteristics of guzheng audio, the study clarifies the performance of its timbre across different frequency bands and the distribution of resonance peaks. This research reveals the complexities of guzheng’s timbre, and the challenges posed by digital transformation, proposing solutions for optimizing spectral models and resonance data processing. The findings provide theoretical support and technical guidance for digital recording, music creation, preservation, and transmission of the guzheng. 展开更多
关键词 GUZHENG Digital transformation spectral Analysis Resonance Characteristics Acoustic Measurement
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Spectrally Efficient Multi-Carrier Modulation Using Gabor Transform
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作者 Shravan Sriram Naveenkumar Vijayakumar +3 位作者 P. Aditya Kumar Akash S. Shetty V. P. Prasshanth K. A. Narayanankutty 《Wireless Engineering and Technology》 2013年第2期112-116,共5页
Non Orthogonal Frequency Division Multiplexing (NOFDM) systems make use of a transmission signal set which is not restricted to orthonormal bases unlike previous OFDM systems. The usage of non-orthogonal bases general... Non Orthogonal Frequency Division Multiplexing (NOFDM) systems make use of a transmission signal set which is not restricted to orthonormal bases unlike previous OFDM systems. The usage of non-orthogonal bases generally results in a trade-off between Bit Error Rate (BER) and receiver complexity. This paper studies the use of Gabor based on designing a Spectrally Efficient Multi-Carrier Modulation Scheme. Using Gabor Transform with a specific Gaussian envelope;we derive the expected BER-SNR performance. The spectral usage of such a NOFDM system when affected by a channel that imparts Additive White Gaussian Noise (AWGN) is estimated. We compare the obtained results with an OFDM system and observe that with comparable BER performance, this system gives a better spectral usage. The effect of window length on spectral usage is also analyzed. 展开更多
关键词 Non-Orthogonal FREQUENCY DIVISION MULTIPLEXING (NOFDM) spectrally EFFICIENT FREQUENCY DIVISION MULTIPLEXING (SEFDM) GABOR transform OFDM Reisz Bases Multi Carrier Modulation (MCM)
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复谱映射下融合高效Transformer的语音增强方法 被引量:7
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作者 张天骐 罗庆予 +1 位作者 张慧芝 方蓉 《信号处理》 CSCD 北大核心 2024年第2期406-416,共11页
针对卷积神经网络(Convolutional Neural Network,CNN)过去在语音增强中表现优异但对全局特征捕获不足,以及Transformer近年展现出长序列间依赖优势但又存在局部细节特征丢失、参数量大等问题,该文为了充分利用CNN与Transformer的优势... 针对卷积神经网络(Convolutional Neural Network,CNN)过去在语音增强中表现优异但对全局特征捕获不足,以及Transformer近年展现出长序列间依赖优势但又存在局部细节特征丢失、参数量大等问题,该文为了充分利用CNN与Transformer的优势并弥补各自不足,提出了一种在复频谱映射下的新型卷积模块与高效Transformer融合的单通道语音增强网络。该网络由编码层、传输层与双分支解码层组成:在编解码部分设计了一种协作学习模块(Collaborative Learning Block,CLB)来监督交互信息,在减少参数量的同时提高主干网络对复特征的获取能力;传输层中则提出一种时频空间注意Transformer模块分别对语音子频带和全频带信息建模,充分利用声学特性来模拟局部频谱模式并捕获谐波间依赖关系。将该模块进一步与通道注意分支相结合,设计了一种可学习的双分支注意融合(Dual-branch Attention Fusion,DAF)机制,从空间-通道角度提取上下文特征以加强信息的多维度传输;最后,在此基础上搭建一种高斯加权渐进网络作为中间传输层,通过堆叠DAF模块进行加权求和后输出以充分利用深层特征,使得解码过程更具鲁棒性。分别在英文VoiceBank-DEMAND数据集、中文THCHS30语料库与115种环境噪声下进行消融以及综合对比实验,结果表明,该文方法仅以最小0.68×10^(6)的参数量,相比于大部分最新相关网络模型取得了更优的主、客观指标,具有较为突出的增强性能与泛化能力。 展开更多
关键词 语音增强 复频谱映射 高效transformer 轻量型网络
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面向高光谱医学图像分类的空-谱自注意力Transformer 被引量:3
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作者 李远 时旭 +2 位作者 杨正春 谭崎娟 黄鸿 《光学精密工程》 EI CAS CSCD 北大核心 2023年第18期2752-2764,共13页
高光谱成像技术的飞速发展给非侵入式医学成像带来新的契机,但高光谱医学图像具有高维度、高冗余以及“图谱合一”的特点,亟需针对上述特点设计智能诊断算法。近年来,Transformer已经在高光谱医学图像处理领域得到广泛应用。然而,不同... 高光谱成像技术的飞速发展给非侵入式医学成像带来新的契机,但高光谱医学图像具有高维度、高冗余以及“图谱合一”的特点,亟需针对上述特点设计智能诊断算法。近年来,Transformer已经在高光谱医学图像处理领域得到广泛应用。然而,不同仪器设备、不同采集操作所获得的高光谱医学图像差异较大,这给现有Transformer诊断模型的实际应用带来了巨大挑战。针对上述问题,本文提出了一种空-谱自注意力Transformer(S3AT),自适应挖掘像素与像素间、波段与波段间的内蕴联系,并在分类阶段融合多个视野下的预测结果。首先,在Transformer编码器中,设计一种空-谱自注意力机制,获取不同视野下高光谱图像上的关键空间信息和重要波段,并将不同视野下所获得的空-谱自注意力进行融合。其次,在模型分类阶段,将不同视野下的预测结果根据可学习权重进行加权融合,对图像进行综合预测。在In-vivo Human Brain和BloodCell HSI两个数据集上,本文算法总体分类精度分别达到82.25%和91.74%。实验结果表明,所提出的算法有效改善高光谱医学图像分类性能。 展开更多
关键词 高光谱医学图像 transformER 空-谱自注意力 预测融合
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基于光谱-空间联合Transformer模型的黄河三角洲湿地高光谱影像分类 被引量:2
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作者 辛紫麒 李忠伟 +3 位作者 王雷全 许明明 胡亚斌 梁建 《海洋科学》 CAS CSCD 北大核心 2023年第5期90-101,共12页
黄河三角洲湿地地物类型在光谱曲线上差异较小,且在空间上分布零散,呈破碎化特性。现有的分类方法受限于局部感受野难以捕捉到图像的长距离依赖关系,导致在黄河三角洲湿地高光谱影像中分类精度不理想,针对此问题,本文提出了一种光谱-空... 黄河三角洲湿地地物类型在光谱曲线上差异较小,且在空间上分布零散,呈破碎化特性。现有的分类方法受限于局部感受野难以捕捉到图像的长距离依赖关系,导致在黄河三角洲湿地高光谱影像中分类精度不理想,针对此问题,本文提出了一种光谱-空间联合Transformer模型。光谱和空间支路分别以光谱向量和空间邻域为输入,基于自注意力机制提取全局光谱和空间特征,在两个支路引入多阶特征交互层,实现浅层边缘信息和深层语义信息的融合,最后采用自适应相加的方式将两路特征融合,送入分类器实现最终分类。本文在黄河三角洲湿地高分五号GF-5和CHRIS两幅高光谱影像上验证方法的有效性,实验结果表明,该方法显著提高了湿地分类的精度,在选用3%的样本训练条件下总体精度分别达到了90.90%和94.17%,优于其他分类方法。研究结果可实现黄河三角洲湿地地物类型的高精度分类,为湿地的保护提供技术支持。 展开更多
关键词 黄河三角洲湿地 高光谱影像分类 transformer模型 光谱-空间联合
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基于Transformer特征提取的A型恒星光谱子型分类算法 被引量:1
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作者 李双川 屠良平 +1 位作者 李馨 王莉莉 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2023年第5期1575-1581,共7页
恒星光谱分类是恒星光谱分析的重要工作之一。我国大型巡天项目LAMOST能够获得海量的恒星光谱数据,为了对海量恒星光谱数据进行高效分类,特别是对恒星光谱子型数据进行分类,需要研究快速有效的恒星光谱自动分类算法。提出一种基于Transf... 恒星光谱分类是恒星光谱分析的重要工作之一。我国大型巡天项目LAMOST能够获得海量的恒星光谱数据,为了对海量恒星光谱数据进行高效分类,特别是对恒星光谱子型数据进行分类,需要研究快速有效的恒星光谱自动分类算法。提出一种基于Transformer特征提取的混合深度学习算法Bert+svm(简记为Besvm)实现A型恒星光谱子型的自动分类。该算法将A型恒星光谱26个线指数作为输入特征,应用Bert模型对26个线指数进行更深层次的学习,通过学习26个线指数的内在关联,进而提取到更有利于A型恒星光谱子型分类的特征。提取好的新特征被输入到分类器算法支持向量机(简记为SVM)中,进而对A型恒星光谱的三个子型A1、 A2和A3进行自动分类。此前,SVM算法在恒星光谱分类任务中已经有过应用,一些衍生的SVM算法在恒星光谱分类任务中也有较高的分类正确率。相比从前应用到恒星光谱分类任务的SVM算法,我们的混合深度学习算法受数据的信噪比影响较小,使用低信噪比数据也能有较高的分类正确率,并且所用数据量较少。通过五组实验验证了该算法的有效性和优越性:实验1用来对比选择优秀的核函数,通过光谱数据的匹配实验,最终选择了径向基核函数RBF;实验2对比了Besvm算法和其他四种传统优秀算法的性能指标,验证了Besvm算法的优越性;实验3用来检验Besvm算法的稳定性;实验4分析了数据量对Besvm算法的影响;实验5分析了不同信噪比数据对Besvm算法分类正确率的影响。综合实验结果分析表明,提出的混合深度学习算法Besvm在规模较小且信噪比低的数据集上仍能保持较高的分类正确率。Besvm总体分类错误率在0.01以下,远低于经典传统机器学习算法LDA算法,BP神经网络算法,SVM算法和Xgboost算法的分类错误率0.7, 0.66, 0.65, 0.36.需要说明的是BP神经网络算法的分类正确率过于受限于隐层神经元的个数。 展开更多
关键词 transformER Bert SVM 光谱分类 线指数 LAMOST
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融合Transformer和VGG网络的高光谱图像分类 被引量:2
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作者 张明慧 周浩 王先旺 《传感器与微系统》 CSCD 北大核心 2023年第12期142-145,150,共5页
在高光谱图像(HSI)光谱数据中,相邻波段间信息的相关性对光谱特征近似的不同地物的分析具有重要意义。然而在传统卷积神经网络(CNN)的HSI光谱数据处理方法中,所提取的特征忽略了不同波段间信息的关联性。提出了一种融合Transformer和VG... 在高光谱图像(HSI)光谱数据中,相邻波段间信息的相关性对光谱特征近似的不同地物的分析具有重要意义。然而在传统卷积神经网络(CNN)的HSI光谱数据处理方法中,所提取的特征忽略了不同波段间信息的关联性。提出了一种融合Transformer和VGG网络的高光谱图像分类方法(SST_Like)。采用3D卷积核的VGG网络提取空间光谱特征,基于多头自注意力(MSA)机制的Transformer网络提取连续光谱间信息,形成空谱联合特征,最终通过多层感知机(MLP)完成地物分类任务。本文提出的SST_Like网络模型在3个HSI开放数据集上的实验结果表明,与传统基于CNN的HSI分类算法相比,可以提取更加深层的、判别性的特征,具有较高的分类性能。 展开更多
关键词 VGG网络 高光谱图像分类 transformER 空谱联合特征提取
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高光谱图像去噪的稀疏空谱Transformer模型 被引量:1
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作者 杨智翔 孙玉宝 +1 位作者 白志远 栾鸿康 《电子测量技术》 北大核心 2024年第1期150-158,共9页
现阶段Transformer模型的应用提升了高光谱图像去噪的性能,但原始Transformer模型对图像空间-光谱耦合关联性的利用仍存在不足;对空间特征的处理存在过于平滑,容易丢失小尺度结构的现象;同时在光谱维度上也过于关注全部通道特征,缺乏对... 现阶段Transformer模型的应用提升了高光谱图像去噪的性能,但原始Transformer模型对图像空间-光谱耦合关联性的利用仍存在不足;对空间特征的处理存在过于平滑,容易丢失小尺度结构的现象;同时在光谱维度上也过于关注全部通道特征,缺乏对不同光谱波段间差异性的利用;为了应对这些问题,本文提出了一种新的稀疏空谱Transformer模型,提升了对空谱耦合关联性的利用。在空间维度,引入局部增强模块增强空间特征细节,应对过平滑问题;同时在光谱维度上提出了Top-k稀疏自注意力机制,自适应选择前K个最相关的光谱通道特征进行特征交互,从而能够有效捕获空谱特征。最终通过稀疏空谱Transformer的层级残差连接实现高光谱图像的去噪。在ICVL数据集上分别对高斯噪声和复杂噪声进行去噪处理,峰值信噪比分别达到40.56 dB和40.19 dB,证明了本文提出的稀疏空谱Transformer模型优越的性能。 展开更多
关键词 高光谱图像去噪 空间-光谱联合特征 稀疏transformer
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Preparation, spectral characteristics and photocatalytic activity of Eu^(3+)-doped WO_3 nanoparticles 被引量:5
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作者 王聪 曹林 《Journal of Rare Earths》 SCIE EI CAS CSCD 2011年第8期727-731,共5页
Eu3+-WO3 nanoparticles were successfully prepared by the modified method of Pechini. The prepared samples were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), high resolution tra... Eu3+-WO3 nanoparticles were successfully prepared by the modified method of Pechini. The prepared samples were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), and UV-vis spectroscopy. Results showed that the Eu3+-WO3 nanoparticles, which had an average external diameter of 10–25 nm, were composed of the different shapes of puncheon and catenary after being pretreated by pH, pressure vessal, and surfactant. Moreover, structural transformation matrix contained different crystals of anorthic and orthorhombic structure. The photocatalytic activities of the nanoparticles were evaluated by photocatalytic decomposition of rhodamine B. Eu3+-WO3 nanoparticles were more efficient than WO3 and TiO2 on sunlight use ratio. Photocatalysis experiments indicated that the Eu3+-WO3 nanoparticles exhibited the highest photocatalytic activity. 展开更多
关键词 structural transformation spectral characteristics PHOTOCATALYSIS Eu3+-WO3 rare earths
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Q-factor estimation in CMP gather and the continuous spectral ratio slope method 被引量:6
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作者 Wu Zong-Wei Wu Yi-Jia +1 位作者 Guo Si Xu Ming-Hua 《Applied Geophysics》 SCIE CSCD 2018年第3期481-490,共10页
The attenuation factor or quality factor(Q-factor or Q) has been used to measure the energy attenuation of seismic waves propagating in underground media. Many methods are used to estimate the Q-factor. We propose a m... The attenuation factor or quality factor(Q-factor or Q) has been used to measure the energy attenuation of seismic waves propagating in underground media. Many methods are used to estimate the Q-factor. We propose a method to calculate the Q-factor based on the prestack Q-factor inversion and the generalized S-transform. The proposed method specifies a standard primary wavelet and calculates the cumulative Q-factors; then, it finds the interlaminar Q-factors using the relation between Q and offset(QVO) and the Dix formula. The proposed method is alternative to methods that calculate interlaminar Q-factors after horizon picking. Because the frequency spectrum of each horizon can be extracted continuously on a 2D time–frequency spectrum, the method is called the continuous spectral ratio slope(CSRS) method. Compared with the other Q-inversion methods, the method offers nearly effortless computations and stability, and has mathematical and physical significance. We use numerical modeling to verify the feasibility of the method and apply it to real data from an oilfield in Ahdeb, Iraq. The results suggest that the resolution and spatial stability of the Q-profile are optimal and contain abundant interlaminar information that is extremely helpful in making lithology and fluid predictions. 展开更多
关键词 Quality FACTOR PRESTACK Q ESTIMATION generalized S transform spectral ratio SLOPE METHOD Q versus offset
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基于频谱特征混合Transformer的红外和可见光图像融合 被引量:2
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作者 陈子昂 黄珺 樊凡 《计算机应用研究》 CSCD 北大核心 2024年第9期2874-2880,共7页
为了解决传统红外与可见光图像融合方法对细节与频率信息表征能力不足、融合结果存在模糊伪影的问题,提出一种基于频谱特征混合Transformer的红外和可见光图像融合算法。在Transformer的基础上,利用傅里叶变换将图像域特征映射到频域,... 为了解决传统红外与可见光图像融合方法对细节与频率信息表征能力不足、融合结果存在模糊伪影的问题,提出一种基于频谱特征混合Transformer的红外和可见光图像融合算法。在Transformer的基础上,利用傅里叶变换将图像域特征映射到频域,设计了一种新的复数Transformer来提取源图像的深层频域信息,并与图像域特征进行混合,以此提高网络对细节与频率信息的表征能力。此外,在图像重建前设计了一种新的令牌替换模块,动态评估Transformer令牌的显著性后消除得分较低的令牌,防止融合图像出现伪影。在MSRS数据集上进行的定性和定量实验结果显示,与九种先进的算法相比,该算法具有较好的融合效果。 展开更多
关键词 图像融合 transformER 频谱特征 红外图像 可见光图像
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Hyper-spectral characteristics of rolled-leaf desert vegetation in the Hexi Corridor, China 被引量:2
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作者 WEI Huaidong YANG Xuemei +4 位作者 ZHANG Bo DING Feng ZHANG Weixing LIU Shizeng CHEN Fang 《Journal of Arid Land》 SCIE CSCD 2019年第3期332-344,共13页
Desert plants survive harsh environment using a variety of drought-resistant structural modifications and physio-ecological systems.Rolled-leaf plants roll up their leaves during periods of drought,making it difficult... Desert plants survive harsh environment using a variety of drought-resistant structural modifications and physio-ecological systems.Rolled-leaf plants roll up their leaves during periods of drought,making it difficult to distinguish between the external structures of various types of plants,it is therefore necessary to carry out spectral characteristics analysis for species identification of these rolled-leaf plants.Based on hyper-spectral data measured in the field,we analyzed the spectral characteristics of seven types of typical temperate zone rolled-leaf desert plants in the Hexi Corridor,China using a variety of mathematical transformation methods.The results show that:(1)during the vigorous growth period in July and August,the locations of the red valleys,green peaks,and three-edge parameters,namely,the red edge,the blue edge,and the yellow edge of well-developed rolled-leaf desert plants are essentially consistent with those of the majority of terrestrial vegetation types;(2)the absorption regions of liquid water,i.e.,1400-1500 and 1600-1700 nm,are the optimal bands for distinguishing various types of rolled-leaf desert plants;(3)in the leaf reflectance regions of 700-1250 nm,which is controlled by cellular structure,it is difficult to select the characteristic bands for differentiation rolled-leaf desert vegetation;and(4)after processing the spectral reflectance curves using a first-order differential,the envelope removal method,and the normalized differential ratio,we identify the other characteristic bands and parameters that can be used for identifying various types of temperate zone rolled-leaf desert plants,i.e.,the 510-560,650-700 and 1330-1380 nm regions,and the red edge amplitude.In general,the mathematical transformation methods in the study are effective tools to capture useful spectral information for species identification of rolled-leaf plants in the Hexi Corridor. 展开更多
关键词 rolled-leaf desert VEGETATION spectral CHARACTERISTICS mathematical transformation VEGETATION identification Hexi CORRIDOR
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Application of Wavelet Algorithm to Spectral Analysis of Oceanic Waves and Offshore Structure Responses 被引量:2
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作者 徐继文 王言英 《China Ocean Engineering》 SCIE EI 2009年第4期635-644,共10页
Fourier transform (FF) is a commonly used method in spectral analysis of ocean wave and offshore structure responses, but it is not suitable for records of short length. In this paper another method, wavelet transfo... Fourier transform (FF) is a commonly used method in spectral analysis of ocean wave and offshore structure responses, but it is not suitable for records of short length. In this paper another method, wavelet transform (WT), is applied to 'analyze the data of short length. The Morlet wavelet is employed to calculate the spectra density functions for wave records and simulated Floating Production Storage and Offloading (FPSO) vessels' responses. Computed wave data include simulated wave data based on JONSWAP spectrum and the recorded data of Storm 149 from North Alwyn. Wavelet method is validated by comparing the statistical characteristics by WF method and those by fast Fourier transform (FFT) method with those of target spectra. The spectral density fnnctions' shapes calculated by WT are less malformed and have less error of statistical characteristics compared with those by FT especially when the record lengths decrease. 展开更多
关键词 spectral analysis wavelet transform fast Fourier transform small sample SIMULATION wave response
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