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关于时频分布的跳频信号参数检测方法研究，短时傅立叶变换、魏格纳变换等-On the time-frequency distribution of the frequency-hopping signal detection parameters, short-time Fourier transform, Wigner-Ville transform, etc.
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三种非平稳信号时频分析的方法 窗口傅里叶变换、wigner分布和小波变换-Three non-stationary time-frequency analysis window Fourier transform, wigner distribution and wavelet transform
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一种基于互局部化Wigner—Ville分布的瞬时频率估计-Based on each local Wigner-Ville distribution of the instantaneous frequency estimation
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基于时频分布的跳频信号分析研究，短时傅立叶变换，魏格纳分布，伪魏格纳分布，平滑伪魏格纳分布-Based on the distribution of time-frequency analysis of frequency hopping signals, short-time Fourier transform, Wigner distribution, pseudo-Wigner distribution, smoothed pseudo-Wigner distribution
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这是一篇现代通信原理课程的作业报告.题目为几种时频分析方法比较及应用.详细介绍了短时傅里叶变换、小波变换、魏格纳—威利分布和Cohen类时频分布这4种典型时频分析方法,并作了比较-This is a modern communication Principle operating report. Entitled Comparison of several time-frequency analysis and 应用. 详细 Jieshao the short time Fourier tran
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"Analysis of Low Probability Of Intercept (LPI) radar signals using Wigner distribution" by Jen-Yu Gau
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discr iption of smoothed psedo wigner ville distribution
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从脑电信号的分析出发,论述了频域分析、时域分析等脑电图分析中常用的信号分析方法和特点,特别介绍了Wigner分布、小波变换和匹配跟踪等时频分析方法、人工神经网络和非线性动力学方法在脑电信号分析和处理中的应用情况。
-From the analysis of eeg, discusses the frequency domain and time domain analysis analysis in the analysis of the commonly used eeg signal a
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将高阶时频表示引入机械故障诊断领域。介绍了Wigner 高阶矩谱(WHOS)的概念、定义。针对多分量信号Wigner 高阶矩谱的交叉项会产生“虚假信号”,结合局域波法, 提出了一种抑制WHOS交叉项的新方法。首先对复杂信号进行预处理, 利用局域波分解方法把其分解成有限个具有单分量特性的基本模式分量,然后对每个基本模式分量计算WHOS。该方法能有效抑制WHOS时频分布的交叉项。通过仿真实验和转子的故障实验,以Wigner 双谱为例, 验证了该方法的实用性,为故障诊断的特征提取提供了新的工具-Hig
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该文提出一种基于广义分数阶傅里叶变换和分数低阶Wigner-Ville 分布的数字调制识别新方法，该方法提取广义分数阶傅里叶变换的零
中心归一化瞬时幅度谱密度的最大值和分数低阶Wigner-Ville 分布幅度的最大值作为识别特征参数，并采用判决树分类器，实现了非高斯噪声下数字调制信号识别。-This paper presents a generalized fractional Fourier transform and fractional lower order Wigner-Vill
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The program computes the Wigner-Ville Distribution using a real signal which is turned into discrete-time analytic signal using Hilbert transform.
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The program computes the Wigner-Ville Distribution using a real signal which is turned into discrete-time analytic signal using Hilbert transform. The computation of WVD is different than in Wigner-Ville Distribution.rar
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The report contains sourses and pictures. The program contains two sources. The first one computes the Wigner Distribution (second-order). The second one computes the Wigner Distribution with Choi-Williams filtering.
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it is very useful for designing lms and wigner function and choes distribution functio inorder to remove the cross terms in the wigner function
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analisis WVD wigner ville distribution
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There a lot of time–frequency methods used for studying the time–frequency distribution of the nonlinear and non-stationary signal, such as short time Fourier transform (STFT) (Zhang and Bao, 1998), Wavelet transform (WT) (Hu et al., 2009), S-transfo
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