xunhuandb2IDWT

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)

《小波十讲（修订版）》主要内容简介：原书《小波十讲》（ten lectures on wavelets）是一本世界范围公认的经典学术名著，是当代数学著作中一本影响巨大的绝妙好书。(text book for wavelet analysis)

利用全局去噪和分层去噪实现信号的小波去噪，实现成功(Implementation of wavelet denoising, global denoising and level-dependent denoising)

这是一本关于高维(三维以上)小波的书，对做三维的朋友应该有参考价值，所以特意贡献出(This is one of the high-dimensional (3-D above) wavelet, the book right to do 3D friends should have reference value, So deliberately contributing)

理解有源滤波器的工作原理、性能特点。学习有源滤波器的设计方法。(Understand the working principle of active filter performance characteristics. Learning active filter design methods.)

实现盲源信号的分离，在一个信号源中提取出有用的信号。(Blind source signal separation, in a signal source to extract useful signals.)

一篇很好的小波变换英文入门资料，附有注释，对想了解小波变换的初学者十分有益。(A good wavelet transform introductory information in English, annotated, very useful for beginners want to learn wavelet transform.)

小波分解，得到低频系数并求特征熵，可用来对信号进行分选识别(Wavelet decomposition, low coefficient and entropy, which can be used for signal sorting and recognition)

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.)

1.实现非抽样提升小波包三层分解 2.有效解决了小波包分解频带交错问题 3.有效输出频谱图(1 non-sampling improved wavelet packet three decomposition. Effective solution to the wavelet packet decomposition band interlacing problems. Effective output spectrogram)