bande-limination-filter

一个基于小波变换的数据聚类样例 Matlab实现(A sample Matlab based on wavelet transform data clustering)

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 )

小波神经网络在变压器故障诊断中的应用，介绍一种小波神经网络诊断变压器故障的新方法 好文章大家一起分享(Wavelet neural network in fault diagnosis of transformer applications, introduced a wavelet neural network of the new transformer fault diagnosis method of a good article to share)

结合离散小波变换(DWT)技术，利用DWT与HVS相结合的良好特性，探索和建立了一种新的图像质量客观评价方法(taking advantage of the similarities of discrete wavelet transform (DWT) with HVS，a new methods for integrated image quality assessment)

很好的继续教育教材，提升素质必备啊！不可错过！十分的好(Good continuing education materials, enhance the quality of essential ah!)

小波分析程序，包括墨西哥小波morlet小波(Wavelet analysis program)

mamatlab二维离散小波变换，应用图像融合(mamatlab two-dimensional discrete wavelet transform, image fusion)

关于小波分析的程序，用于分析振动信号的程序，很好用(Wavelet analysis on the procedures used to analyze the vibration signal of procedures, very good use)

短时傅里叶变换 快速傅里叶变换对音频信号处理 频谱分析 (fast fft )

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)