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利用子波变换的多分辨率分析方法,将遥感光谱分解为反映目标结构概貌的模糊信号和刻划目标结构细节的锐化信号。结果表明:对目标特征的分析,小波变换方法比FFT更为敏感。 相似文献
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子波变换技术是当今世界数字信号处理等学科领域研究的热点之一。本文介绍了子波变换技术的发展概况,论述了子波变换的基本原理和基本方法,并分析了该技术在信号时频分析中的优越性。 相似文献
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利用子波变换的多分辨率分析方法,将遥感光谱分解为反映目标结构概貌的模糊信号和刻划目标结构细节的锐化信号,结果表明:对目标特征的分析,小波变换方法比FFT更为敏感。 相似文献
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信号时频分析对电子战侦察有重要意义。子波变换被认为对此有极大价值。对于波变换及其应用展开讨论。着重论述了子波变换的起源背景、子波变换是否无所不能和单尺度哈尔(Haar)子波平移变换检测信号瞬时频率,并对用于波变换脊分析无线电信号的方法所存在的局限性进行简要讨论。 相似文献
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利用子波变换检测瞬时信号 总被引:18,自引:1,他引:17
本文提出一种基于子波变换的检测瞬时信号的方法。推导出一种适合于检测瞬时信号的子波基函数,并将其应用于检测波形和到达时间未知的瞬时信号,利用子波的伸缩和时移特性,通过对信号做多尺度的子波变换,可以在低信噪比下很好地检测到信号,本文还推导了相应的检测统计量及其统计分布特性,理论分析和计算机模拟结果表明,本方法是有效的,是提高检测性能的一种新途径。 相似文献
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基于子波变换局部极大值的信号去噪新算法 总被引:7,自引:0,他引:7
本文出了一种相尺度间信号子波变换极大值点相似系数的定义,它定量地描述了相邻尺度间子波变换极大点的相似性。在上核实 定主的基础上,提出了波变换域信号去噪的新算法。 相似文献
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莫奈特子波变换分析信号奇点 总被引:1,自引:1,他引:0
用原函数为光滑曲线的子波变换(简称莫奈特子波变换)检测信号波形奇点的方法是建立在信号奇异性与李普西兹正则性关系基础上的。该方法的基本原理是信号子波变换Wψ(a,t)等价于信号光滑版s(t)θa(t)的1阶导数,当s(t)θa(t)为尖锐变化时,必然对应其导数的模的极大值,只要检测到子波变换模的极大值,就能检测到信号s(t)的奇点。仿真表明,莫奈特子波变换能准确检测出信号奇点。 相似文献
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本文首先介绍了子波变换的局部时频分析法。基于子波变抉系数模极大值同信号奇异性之间的关系,给出了一种利用该极大值信息的信号重建方法。由模拟结果可以看出,这种重建方法的精度在-35dB以上。 相似文献
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Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study 总被引:2,自引:0,他引:2
In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined. 相似文献
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Enhancement of spectral analysis of myoelectric signals duringstatic contractions using wavelet methods 总被引:2,自引:0,他引:2
In this paper, we introduce wavelet packets as an alternative method for spectral analysis of surface myoelectric (ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. Our simulation results show that wavelet packet estimate has slightly less mean square error (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give us some advantages over the traditional methods such as multiresolution of frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. We also introduce wavelet shrinkage method for improving spectral estimates by significantly reducing the MSE's for both Fourier and wavelet packet methods. 相似文献
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传统谱相关分类法利用不同信号在a截面上所表现的不同谱相关特征可对通信信号进行分类,需要提取六种特征参数。文章结合小波分析法估计信号的码元宽度Tt,利用谱相关提取的三种特征参数,可对常见八类调制信号进识别。仿真表明,该方法具有很好的识别效果。 相似文献
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提出了一种数字通信信号码元速率的估计算法。对截获接收机输出的调制信号提取基带信号,利用此基带信号小波变换系数的模值,构造与原调制信号码速率一致的单极性脉冲序列。通过对此单极性脉冲序列的功率谱分析可知,在基带信号码元速率的整数倍处存在离散谱线,检测这些离散谱线即实现了信号码元速率的估计。这种算法能在低信噪比下估计信号的码元速率。理论分析和实际信号处理证明了本文提出算法的可行性。 相似文献
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动态纹理在空间和时间上表现出“外观”和“运动”属性,为了有效结合这两种属性进行动态纹理分析,本文提出一种基于时间—顶点谱图小波变换与边缘分布协方差模型的动态纹理分类方法。该方法将动态纹理看成时间—顶点图信号,利用时间—顶点谱图Meyer小波变换对动态纹理进行多尺度分解,再对每个子带应用边缘分布协方差模型,由此得到带内相关性的特征协方差矩阵作为动态纹理特征进行分类。由于时间—顶点图信号的表示可以有效描述动态纹理像素间的空间关系及其沿时间的变化,同时谱图小波变换继承了图表示和小波变换的优势,因此利用时间—顶点谱图小波分解与边缘分布协方差模型,可得到有效的动态纹理特征。在标准动态纹理数据集上的分类实验结果表明,本文方法具有良好的分类性能。 相似文献
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信号的一种快速子波分解 总被引:7,自引:2,他引:5
本文提出一种分析子波g(t),并在此基础上讨论了子波变换的性质和特点,提出复信号的正交子波变换与反变换并讨论了复信号的正交子波分解与恢复,最后给出一种快速算法。 相似文献
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Zhang Yifan He Mingyi 《电子科学学刊(英文版)》2007,24(2):218-224
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR)method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly. 相似文献