搜索资源列表
Hilbert-Huang
- Hillbert-Huang变换是近年来一种新兴的信号分析方法,由于该方法是从信号本身的尺度进行分解,与传统的傅里叶变换方法有着本质的不同,Hilbert-Huang变换在处理非平稳信号方面有着巨大的优势。-Transformation of Hillbert-Huang in recent years a new signal analysis method, because the method is the decomposition of the scale of the signal
hht
- 希尔伯特变换以及进行end分解，将非平稳信号自适应分解-emd decomposition
GaborDecon_test
- 测试gabor反褶程序 地震信号是非平稳信号，其子波是随时间变化的。Gabor反褶积技术地震道切成若干个Gabor 片，在每一片中子波是不变的，因此可以实现将非平稳信号向平稳信号的转换。因此，Gabor反褶积被认为是高分辨率、真振幅反射系数的估计方法。-Test gabor deconvolution procedure Seismic signal non-stationary signals, the wavelet is changing with time. Gabor deco
ceemdan
- 它是一种时频分析方法，能够较好的处理非线性非平稳信号，具有很强的自适应性-It is a time-frequency analysis method, can deal with non-linear non-stationary signal, has a strong self-adaptability.
Procedure91
- 随机减量法的MATLAB程序，用于提取非平稳信号的自由衰减振动-Random decrement technique MATLAB program, free for extracting non-stationary vibration signal attenuation
20161203
- hht变换在处理非线性、非平稳信号方面相对于传统的信号处理手段表现出很好的优越性-Hht transform in the processing of non-linear, non-stationary signal relative to the traditional signal processing means to show good superiority
xinhaoxishubiaoshi
- 信号稀疏表示是一种新兴的信号分析和综合方法，其目的就是在过完备字典中用尽可能少的原子来表示信号。采用时频原子字典的信号稀疏表示能够有效地揭示非平稳信号的时变特征。信号稀疏表示吸引了研究者的大量关注，这种方法已经被应用到信号处理的许多方面，例如非平稳信号分析，信号编码、识别与信号去噪等。-Signal sparse representation is a new method of signal analysis and synthesis, and its purpose is in over-
emd
- 对非线性，非平稳信号进行处理的方法，即经验模态分解方法，处理效果好-The non-linear, non-stationary signal processing method, the empirical mode decomposition method, the treatment effect is good
xujiayshangchuan
- 经验模态分解(Empirical Mode Decomposition,简称EMD)法是美籍华人N. E. Huang等人于1998年提出的，适合于分析非线性、非平稳信号序列，具有很高的信噪比。该方法的关键是经验模式分解，它能使复杂信号分解为有限个本征模函数(Intrinsic Mode Function，简称IMF)，所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。-Empirical Mode Decomposition method (Empirical Mode Dec
kjspfb
- 空间时频分布，既适用于平稳信号的场合又适用于时变、非平稳信号的场合-Spatial time-frequency distribution, both for stationary signal applications and for time-varying, non-stationary signal applications
DOA-Estimation-of-LFM-Signal
- 非平稳信号DOA估计，主要思想是去交叉项，保留自项，形成估计矩阵。-DOA Estimation of LFM Signal
plot_hht
- 对非平稳信号进行模态分解为瞬时频率有实际意义的多个分量，进而用希尔伯特得到个分量的瞬时频谱，测试有效(The modal decomposition of non-stationary signals is effective)
emd+instfreq
- 包括emd分解和instfreq补丁程序，适用于emd分解，处理非平稳信号。(Including EMD decomposition and instfreq patch, EMD decomposition is applied to deal with non-stationary signals.)
EMD
- 经验模态分解(Empirical Mode Decomposition,简称EMD)法是美籍华人N. E. Huang等人于1998年提出的，适合于分析非线性、非平稳信号序列，具有很高的信噪比。该方法的关键是经验模式分解，它能使复杂信号分解为有限个本征模函数(Intrinsic Mode Function，简称IMF)，所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。(Empirical mode decomposition (EMD) is proposed by Chine
fenjie7768
- labview编写的EMD分解程序 经验模态分解方法（EMD）在非平稳信号的分析和处理中起着重要的作用，为了能够方便的使(EMD decomposition program written by LabVIEW, empirical mode decomposition method (EMD) plays an important role in the analysis and processing of non-stationary signals, so as to make it co
frft
- 区别去传统的傅里叶变换，对于非平稳信号而言，分数傅里叶变换是一个较好的方法，本程序实现了分数傅里叶变化对LPF类信号的估计。具有较高的学习价值(Different from the traditional Fourier transform, for non-stationary signals, fractional Fourier transform is a better method, this program implements the fractional Fourier tran
xiaobo
- 用于非平稳信号的处理，可以对信号进行小波分析。(For non-stationary signal processing, wavelet analysis can be carried out on the signal)
声音解析matlab
- 对非平稳信号进行分段、截取，再做短时傅里叶变换，分析其频谱特性，并找到各个时间节点的频率特性，以便分析不同事件段内的声音特征。(The non-stationary signals are segmented and intercepted, and then the short-time Fourier transform is used to analyze their frequency spectrum characteristics, and the frequency charact
STFFTtool
- 对非平稳信号进行分段、截取，将非平稳信号转化为平稳信号，再做短时傅里叶变换，分析其频谱特性，并找到各个时间节点的频率特性，以便分析不同事件段内的声音特征。(The non-stationary signals are segmented and intercepted, and then the short-time Fourier transform is used to analyze their frequency spectrum characteristics, and the fre
STFFTtool1
- 对非平稳信号进行分段、截取，再对处理过后的短时信号做短时傅里叶变换，分析其频谱特性，并找到各个时间节点的频率特性，以便分析不同事件段内的声音特征。(The nonstationary signals are segmented, and then the interception, the short-time signal after processing the short-time Fourier transform, the analysis of the spectrum charac