搜索资源列表
rtcmas_client
- 小波包分析提取振动信号中的特征频率,以及能量谱分析计算-wavelet packet analysis vibration signal from the characteristic frequency, and the energy spectrum analysis
wj
- 利用matlab编写的小波分解分频和除躁程序,分为高低频率,并除去噪声,达到较好的效果。
小波分析--黄变换程序
- 首先,找出 上所有的极值点,然后用三次样条函数曲线循序连接所有的极大值点,得到信号 的上包络线 ,采用同样的方法连接所有的极小值点,得到 的下包络线 。循序连接上、下两条包络线的均值可得到一条均值线 : (7-1) 再用 减去 得到 : (7-2) 如果 满足IMF的两个条件,则 即为第一阶IMF,一般来说, 并不满足条件,此时,
对轴承故障振动信号的matlab小波分析程序
- 对轴承故障振动信号的matlab小波分析程序,能完成对故障特征频率的提取,Of bearing fault vibration signals matlab wavelet analysis procedures, can finish on the fault characteristic frequency extraction
powerspectrum
- 使用小波包变换分析两个信号的特征向量和各频率成分的功率谱-the analysis of two signals eigenvector and power spectrum using wavelet-packet transform
xiaobobaofenjie
- 本程序重构各层低频和高频系数,画功率谱,横坐标为频率,纵坐标为功率,小波包分解最后一句是为显示小波包四层分解树结构-Reconstruction of the procedural layers of low and high frequency coefficients, draw power spectrum, the abscissa is the frequency, the vertical axis is power, wavelet packet decomposition is
wavelet
- matlab小波变换实例,用mallat快速算法将其进行频率分割,最后将低频重组,最后去噪效果-matlab wavelet transform instance, with mallat fast algorithm to the frequency division, and finally to low-frequency reorganization, the final denoising
wavelet
- 应用小波理论进行模态分析,求出固有频率和阻尼比-modal analysis use the wavelet method
waveletpacketsZHH
- wave:小波包分解,对信号进行小波包分解,将信号按频率成分分解出来,并且估计小波包能量-wave: wavelet packet decomposition, wavelet packet decomposition of the signal, the signal decomposition by frequency components out, and the estimated wavelet packet energy
MFCC_DWT
- 基于频率到谱技术的离散小波变换的音频识别技术-Frequency to the spectral techniques based on discrete wavelet transform audio recognition technology
jiangzao
- 小波不同于传统的傅里叶变换和短时傅里叶变换,它具有随信号频率变化的时间频率分析能力,因此可以用来去噪!-This program implement the function of the interference of the noise!
Wavelettransformofthefrequencyseprate
- 利用小波变换将信号中的各频率分开,得到低频信号和高频信号-Wavelet transform of the frequency of the signal separated by low-frequency signal and high frequency signals
progress-in-speech-compression
- 为了满足数字通信及其它商业应用的需求,语音压缩编码技术得到了迅速发展。介绍了目前语音压缩编码技术 的研究进展,主要包括连续可变斜率增量调制(CVSD)、小波分析、多脉冲激励线性预测编码、散布脉冲码激励线性预 测(DP-CELP)、多重脉冲散布非均匀代数码本激励线性预测(MPD-USACELP)、波形内插(Ⅷ)、线谱对(频率)(LSP)的量化-In order to satisfy deman凼of the digital communication and other commercia
xiaobosuanfa
- 采样频率 fs=10000 轴承外环故障信号 fid=fopen( bearingout.dat , r ) 故障 N=1024 xdata=fread(fid,N, int16 ) fclose(fid) xdata=(xdata-mean(xdata))/std(xdata,1) 时域波形 figure(1) plot(1:N,xdata) xlabel( 时间 t/n ) ylabel( 电压 V/v )
小波变换
- 小波变换 信号处理 通过伸缩平移运算对信号(函数)逐步进行多尺度细化,最终达到高频处时间细分,低频处频率细分,能自动适应时频信号分析的要求,从而可聚焦到信号的任意细节。(Wavelet transform signal processing through the telescopic translation operations to signal (function) step by step multi scale refinement, the final breakdown of ti
小波分解重构
- 小波分解重构,可以作为研究小波频率的一个重要参考,但是注意,该代码分解出来的高低频系数不能完全当作滤波器使用,只是参考。(Wavelet decomposition and reconstruction can be used as an important reference for studying wavelet frequency, but attention is paid to the high and low frequency coefficients decomposed by
--4层--db4--20db--
- 小波阈值去噪,小波变换是一种信号的时间——尺度(时间——频率)分析方法,它具有多分辨分析的特点,而且在时频两域都具有表征信号局部特征的能力(Wavelet threshold denoising)
Weak signal detection
- 针对强噪声背景中弱信号检测问题,在传统检测方法基础上,提出了基于联合去噪和频率调制的微弱信号检测方法。搭建自相关和小波阈值变换联合去噪系统,极大程度抑制了噪声对检测结果的不利影响。利用频率可调标准信号调制待测信号频率,使得被测信号与检测系统策动力信号的频率差满足检测条件,打破了利用Duffing 振子检测系统只能检测与系统策动力频率相近信号的限制。(In order to solve the problem of weak signal detection in strong noise bac
Desktop
- 西储大学轴承数据,故障特征频率明显,与理论值基本符合。(The bearing data of Xichuan University have obvious fault characteristic frequency, which is basically in accordance with the theoretical value.)
xiaobo
- 对故障数据的小波包分解与信号重构、小波包能量特征提取 暨 小波包分解后实现按频率大小分布重新排列,并进行降噪处理。(After wavelet packet decomposition and signal reconstruction, wavelet packet energy feature extraction and wavelet packet decomposition, the fault data can be rearranged according to the frequ