▍1. MATLAB
与labview之间的联系 在小波变换方面(Contact between labview in terms of the wavelet transform)
与labview之间的联系 在小波变换方面(Contact between labview in terms of the wavelet transform)
与labview之间的联系 在小波变换方面(Contact between labview in terms of the wavelet transform)
离散小波变换是指在特定子集上采取缩放和平移的小波变换,是一种兼具时域和频域多分辨率能力的信号分析工具。此变换运用可以缩放平移的小波代替固定的窗进行计算分析,主要应用于信号编码和数据压缩。(Discrete wavelet transform refers to the specific subset take scaling and translation on the wavelet transform, is a kind of multi-resolution ability both time domain and frequency domain signal analysis tool. This transformation can use zoom translational wavelet calculation and analysis instead of the fixed window, mainly used in signal coding and data compression. )
离散小波变换是指在特定子集上采取缩放和平移的小波变换,是一种兼具时域和频域多分辨率能力的信号分析工具。此变换运用可以缩放平移的小波代替固定的窗进行计算分析,主要应用于信号编码和数据压缩。(Discrete wavelet transform refers to the specific subset take scaling and translation on the wavelet transform, is a kind of multi-resolution ability both time domain and frequency domain signal analysis tool. This transformation can use zoom translational wavelet calculation and analysis instead of the fixed window, mainly used in signal coding and data compression. )
包含压缩传感的随机矩阵程序,如小波变换和高斯随机矩阵和omp重构算法(Random matrix containing the compressed sensing programs, such as wavelet transform and Gaussian random matrices and omp reconstruction algorithm)
小波方法进行降噪,阈值函数来完成不同设计,核心程序如下面的所示,使用的小波基有coif5,db3,sym4,bior2.4,haar,rbio(Wavelet method for noise reduction, design to complete different threshold function, the core program as shown below, using the wavelet base coif5, db3, sym4, bior2.4, haar, rbio )
小波方法进行降噪,阈值函数来完成不同设计,核心程序如下面的所示,使用的小波基有coif5,db3,sym4,bior2.4,haar,rbio(Wavelet method for noise reduction, design to complete different threshold function, the core program as shown below, using the wavelet base coif5, db3, sym4, bior2.4, haar, rbio )
说明: 2.1 傅里叶变换 2.1.1 经典傅里叶变换 2.1.2 傅里叶变换的基本性质 2.1.3 快速傅里叶变换 2.1.4 短时傅里叶变换 2.2 小波分析与多分辨率分析的历史 2.3 小波分析与傅里叶变换的对比 2.4 小波变换 2.4.1 连续小波变换 2.4.2 离散小波变换 2.4.3 高维小波连续变换 2.5 常用小波基函数 2.5.1 小波函数 2.5.2 小波函数系 2.5.3 复数小波 2.6 构造紧支撑正常小波基 2.7 多分辨率分析与小波构造 2.8 分析小波包 2.8.1 小波包的定义及性质 2.8.2 分解小波包的空间 2.8.3 小波包算法(2.1 Fourier transform 2.1.1 classical Fourier transform 2.1.2 The basic properties of the Fourier transform 2.1.3 Fast Fourier Transform 2.1.4 short time Fourier transform 2.2 wavelet analysis and multi-resolution analysis of the history of 2.3 Wavelet Analysis and comparison of the Fourier transform 2.4 Wavelet Transform 2.4.1 Continuous Wavelet Transform 2.4.2 Discrete Wavelet Transform 2.4.3 Continuous high-dimensional wavelet transform 2.5 Common wavelet basis function 2.5.1 wavelet function 2.5.2 Department of wavelet function 2.5.3 Complex Wavelet 2.6 Construction of compactly supported wavelets normal More than 2.7 resolution analysis and wavelet construction 2.8 Analysis of Wavelet Packet 2.8.1 Definition and properties of wavelet packet 2.8.2 wavelet packet decomposition space 2.8.3 Wavelet Packet Algorithm)
2.1 傅里叶变换 2.1.1 经典傅里叶变换 2.1.2 傅里叶变换的基本性质 2.1.3 快速傅里叶变换 2.1.4 短时傅里叶变换 2.2 小波分析与多分辨率分析的历史 2.3 小波分析与傅里叶变换的对比 2.4 小波变换 2.4.1 连续小波变换 2.4.2 离散小波变换 2.4.3 高维小波连续变换 2.5 常用小波基函数 2.5.1 小波函数 2.5.2 小波函数系 2.5.3 复数小波 2.6 构造紧支撑正常小波基 2.7 多分辨率分析与小波构造 2.8 分析小波包 2.8.1 小波包的定义及性质 2.8.2 分解小波包的空间 2.8.3 小波包算法(2.1 Fourier transform 2.1.1 classical Fourier transform 2.1.2 The basic properties of the Fourier transform 2.1.3 Fast Fourier Transform 2.1.4 short time Fourier transform 2.2 wavelet analysis and multi-resolution analysis of the history of 2.3 Wavelet Analysis and comparison of the Fourier transform 2.4 Wavelet Transform 2.4.1 Continuous Wavelet Transform 2.4.2 Discrete Wavelet Transform 2.4.3 Continuous high-dimensional wavelet transform 2.5 Common wavelet basis function 2.5.1 wavelet function 2.5.2 Department of wavelet function 2.5.3 Complex Wavelet 2.6 Construction of compactly supported wavelets normal More than 2.7 resolution analysis and wavelet construction 2.8 Analysis of Wavelet Packet 2.8.1 Definition and properties of wavelet packet 2.8.2 wavelet packet decomposition space 2.8.3 Wavelet Packet Algorithm)
对含噪声信号进行小波变换;对变换得到的小波系数进行某种处理,以去除其中包含的噪声;对处理后的小波系数进行小波逆变换,得到去噪后的信号(Containing noise signal wavelet transform the wavelet transform coefficients to a treatment to remove the noise contained therein the treated wavelet inverse wavelet transform coefficients to obtain a denoised signal)
希尔伯特变换和小波包结合的齿轮箱故障诊断方法,里面有具体的介绍小波包的分层方法,非常详细,可以下下来看看(Hilbert transform and wavelet packet of gearbox fault diagnosis method, there is detailed introduction inside the layered method of wavelet packet is very detailed, can down and have a look )
希尔伯特变换和小波包结合的齿轮箱故障诊断方法,里面有具体的介绍小波包的分层方法,非常详细,可以下下来看看(Hilbert transform and wavelet packet of gearbox fault diagnosis method, there is detailed introduction inside the layered method of wavelet packet is very detailed, can down and have a look )
一种基于EMD分解后对imf分量利用小波分解进行去噪的方法,给出了相应的例子,有注释(Based on the EMD decomposition after the imf component by using the method of wavelet decomposition denoising, corresponding examples are given, with comments)
一种基于EMD分解后对imf分量利用小波分解进行去噪的方法,给出了相应的例子,有注释(Based on the EMD decomposition after the imf component by using the method of wavelet decomposition denoising, corresponding examples are given, with comments)
小波变换,小波去噪,包含多种去噪方法,模极大值,自适应,阈值去噪(Wavelet transform, wavelet denoising, including multiple Denoising, modulus maxima, adaptive thresholding)
小波变换,小波去噪,包含多种去噪方法,模极大值,自适应,阈值去噪(Wavelet transform, wavelet denoising, including multiple Denoising, modulus maxima, adaptive thresholding)