Autocorrelation

基于小波变换的图片重建 有完整代码 工程 以及说明 涉及到图片的切割(image reconstruction based on wavelet translate )

对信号进行局部均值分解，得到一系列具有物理意义的pf分量(Local mean decomposition of the signal to obtain a series of having a physical meaning PF component)

利用小波包变换对信号进行分解及重构，对于初学者是一个很好的学习材料。(Wavelet packet transform signal decomposition and reconstruction, is a good learning materials for beginners.)

有关小波包分解和介绍的PPT，适合于初学者快速掌握小波包分解相关问题。(the PPT of wavelet packet decomposition and the introduction , suitable for beginners to quickly master the wavelet packet decomposition.)

独立分量分析（ICA）算法编码，盲源信号分离（声音信号的分离）(Independent component analysis (ICA) algorithm coding, Blind Source Separation (voice signal separation))

小波包分解包括重构信号问题程序，这是一个matlab程序，经过测试可用，数据采用自己的数据。(Including the reconstructed signal wavelet packet decomposition problem program, which is a matlab program, tested available data using their own data.)

说明：  计算小波分解后的能量及小波熵。里面还有OFDM信号和WPM信号的程序。(After calculating the energy of wavelet decomposition and wavelet entropy. There is also OFDM signal and the WPM signal process.)

应用Matlab进行小波包对时变谐波分析的代码(Matlab Applications for wavelet packet on time-varying harmonic analysis)

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.)

小波变换程序，用于对一维信号，二维信号进行稀疏变换(wavelet transform)