搜索资源列表
Noise-reduction-algorithm
- 对设备进行故障诊断的主要方法就是测量故障 设备的振动或噪声, 并对其进行分析, 从而找出故障原因。然而振动或噪声信号中除了对分析故障有用的信息外, 还有大量的噪声成分。只有有效地滤除噪声, 才能获得有用的信息, 从而得到可靠的分析结论。传统的滤噪方法是将被噪声污染的信号通过一个滤波器, 滤掉噪声频率成分。但对于短时瞬态信号、非平稳信号、含宽带噪声的信号, 采用传统处理方法有着明显的局限性。小波变换为信号去噪提供了一种有效的方法, 小波阈值去噪具有传统方法不可比拟的优越性。但是小波分解的频域重
Local-waveanalysis-of-the-law
- 为了克服傅氏变换不能同时保留信号的时间 信息和频率信息的缺点,人们引进了局域波法,它是最近发展起来的处理非线性、非平稳信号的时频分析方法,通过对信号局部特征出发,直接由信号本身构造基函数,具有良好的局部适应性-In order to overcome the Fourier transform of the shortcomings of the time and frequency information of the signal can not be reserved, the int
st
- S变换的源程序,具有很好的时频解析功能,处理非平稳信号的有力武器-S transform source code, a powerful weapon to have good time-frequency analysis, processing non-stationary signals
eemdtaiwan
- 台湾的一个改进的EMD对非平稳信号进行预处理,据说挺好用,不太会用-Taiwan, an improved EMD pretreatment of non-stationary signals, is said to very good use, and less likely to use
STRUCTURAL-BREAKS-ESTIMATION
- 基于遗传算法的断点估计,对非平稳信号进行分段,使其分段平稳,便于对信号的处理,尤其对于语音信号,非常常用-Based on genetic algorithms breakpoint estimates for non-stationary signal segment, making it piecewise smooth, easy signal processing, especially for the speech signal, very common
plot_hht_3d
- 对于非平稳信号,用emd分解后,进行hibert变换后,输出时频三维图,-Output frequency of the three-dimensional map
EMD
- 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,为了能够方便的使用EMD方法对信号进行处理,现将LabVIEW虚拟仪器开发平台良好的用户图形界面和MATLAB软件强大的数值分析功能相结合,利用LabVIEW调用MATLAB实现EMD信号处理方法。仿真结果表明对信号进行EMD分解后,使得瞬时频率具有了物理意义,但只是对信号进行了初步处理,可根据实际需要进行相应后续处理。-the labview written EMD decomposit
Wavelet-analysis
- 小波分析~语音识别 非平稳信号的处理 小波变换 谱分析-Wavelet analysis ~speech recognition
EMD-decomposition-programe
- Hilbert-Huang变换之EMD分解程序。可以直接运行,以及附有几个详细例子。可以用以对非线性非平稳信号的处理,效果理想。-Hilbert-Huang transform EMD decomposition process. Can be run directly, as well as with several detailed examples. Can be used for non-linear non-stationary signal processing, the resul
package_emd
- 经验模态分解emd,HIlbert变换工具箱,用以处理非线性非平稳信号,时频分析。-Empirical mode decomposition emd Hilbert transform toolbox for nonlinear and non-stationary signals, time-frequency analysis.
matlabEMD
- matlab程序 EMD分解,经本人测试非常好用,可用于振动信号分解,平稳或非平稳信号都可以。-EMD decomposition matlab program, after I test is very easy to use, can be used for vibration signal decomposition, stationary or non-stationary signal can be.
hmm
- 隐马尔可夫过程是一个双重随机过程:一重用于描述非平稳信号的短时平稳段的统计特 征(信号的瞬态特征,可直接观测到);另一重随机过程描述了每个短时平稳段是如何转变 到下一个短时平稳段,即短时统计特征的动态特性(隐含在观察序列中)-Hidden Markov process is a doubly stochastic process: a weight used to describe the non-stationary signal short plateau statistical S
unstable
- 非平稳信号的功率谱估计,这个我以前用过的很好使-Non-stationary signal power spectrum estimation, that I' ve used so good
Order-Spectral-Analysis
- 用于起停车过程中的阶次谱分析 可以实现非平稳信号的分析诊断-Parking for starting the process of the order of the spectral analysis of non-stationary signal can be achieved analysis and diagnosis
COT
- 关于阶比分析的文献,阶比分析广泛应用与非平稳信号中,希望有所有帮助-About order analysis literature Order Analysis widely used non-stationary signals, hope to have all the help
3DFRFT
- 三维的分数阶傅立叶变换,用于非平稳信号处理-the 3D Fractional Fourier Transform
117
- 针对非线性非平稳信号的去噪问题,提出一种基于主成分分析(PCA)的经验模态分解(EMD)消噪方法.该方法根据EMD的分解特性,利用PCA对噪声信号经EMD分解后的内蕴模态函数(IMF)进行去噪处理-For nonlinear and non-stationary signal de-noising is proposed based on principal component analysis (PCA) of the empirical mode decomposition (EMD) de
lmd
- 局部均值分解是由Smith提出的一种新的非线性和非平稳信号分析方法。由于LMD是依据信号本身的信息进行自适应分解的,产生的PF分量具有真实的物理意义,由此得到的时频分布能够清晰准确地反映出信号能量在空间各尺度上的分布规律。-Local mean decomposition is a new nonlinear and non-stationary signal analysis method proposed by the Smith. Since LMD information is base
(HOSA)Toolbox
- 高阶谱分析,很实用,能帮助分析非平稳信号-Higher order spectral analysis, it is useful to help analyze non-stationary signals
tftb-0.1
- 分析非平稳信号的工具包,时频工具包,能帮你分析非平稳信号-Analysis Toolkit non-stationary signals, time-frequency toolkit can help you analyze non-stationary signals