watermark_image

二代小波harr变换整数小波变换，适合图像处理专业人员参考(Second generation wavelet transform Harr integer wavelet transform for image processing professionals reference)

275hz正弦波激励程序，用于模拟波的激发，适用于导波及其他方面，matlab程序(275hz sine wave incentive program for the simulation of wave excitation applied to guide spread to other aspects, matlab program)

实现db6小波提升变换，对信号进行5层分解和重构。另外被屏蔽的部分为离散小波变换。(Enhance the realization of wavelet transform db6, 5 layers of signal decomposition and reconstruction. In addition to being part of shielding DWT.)

用卷积深度置信网络CDBN的方法来处理睡眠EEG;(use Convolutional deep belief networks to sleep EEG)

基于TS变换（一种整数变换）所实现的脆弱数字水印方法，讨论了整数水印在数字水印中的优点(transform (a Integer Transform), the fragile digital watermarking methods, Integer discussed in the digital watermark of the benefits of watermarking)

基于matlab小波变换的轴承故障外圈点蚀分析。(Based on wavelet transform matlab punctuate eclipse outer bearing failure analysis.)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

说明：  提出了一种基于复解析小波变换的相位诊断齿轮故障的方法。复解析小波变换将Hilbert变换与小波分析紧密结合在一起,具有自适应分析能力。利用复解析小波变换得到齿轮振动信号的相位,其功率谱图上可提取调制边频带结构来识别故障模式。试验结果表明这种方法可有效应用于齿轮局部故障诊断中。(A new method using the phase based on complex analytical wavelet transform for fault diagnosis of gears was proposed. The phase of vibration signals of gears is got by complex analytical wavelet transform, which combines Hilbert transform with wavelet transform tightly and possesses adaptive analysis ability. By making spectrum analysis of the phase, the sideband structure in power spectrum can be protruded, and the fault pattern can be identified. Experimental results show that the proposed method is effective in local defect detection of gears.)

说明：  小波标架的共轭梯度算法（Mallat，信号处理的小波导引）(Conjugate gradient algorithm for computing daul function.)

小波变换(wavelet transform，WT)是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的"时间-频率"窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间(空间)频率的局部化分析，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，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(Wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform and overcomes the shortcomings that window size does not vary with frequency. It can provide a frequency-dependent The Time-Frequency window is ideal for time-frequency analysis and processing of signals. Its main feature is that by transforming some features that can fully highlight some aspects of the problem, the localization of the time (space) frequency can be analyzed, and the signal (function) can be gradually and multi-scale refined by the scaling operation, finally reaching the high frequency Time subdivision, frequency subdivision at low frequencies, can automatically adapt to the requirements of time-frequency signal analysis, which can focus on any details of the signal to solve the difficulties of Fourier transform has become a major breakthrough in the scientific method since Fourier transform.)