Imagefusion

使用wavelet 將影像分解 再利用threshold方法去雜訊(use wavelet to denoised in a picture)

语音信号去噪，在MATLAB开发环境下，对含噪声的语音信号进行小波变换，实现语音增强的功能。(The speech signal denoising, wavelet transform, the noisy speech signal in the MATLAB development environment, Speech enhancement functions.)

循环平稳信号是一类特殊的非平稳信号，其统计特征具有随时间呈周期变化的特点。旋转机械由于周期运行方式其振动信号具有循环平稳特性，因此利用循环平稳分析方法能够提取出在平稳假设下所不能得到的隐藏故障特征信息，为有效地分离和识别旋转机械早期微弱故障特征提供可能。(The cyclostationary signal is a special type of non-stationary signal whose statistical characteristics have a periodic variation with time. Due to the cyclical operation of the rotating machinery, the vibration signal has the characteristics of cyclostationary stability. Therefore, the cyclostationary analysis method can extract the hidden fault feature information that can not be obtained under the stationary assumption, which provides the possibility to effectively separate and identify the early weak fault features of the rotating machinery.)

基于matlab程序对声音信号进行去噪处理，通过小波包处理及小波分析结合(Matlab program based on the sound signal denoising by wavelet packet processing and wavelet analysis combined)

说明：  小波变换技术与工程实践：图像的小波变换(MFC框架下)(Wavelet transform technology and engineering practice: Image Wavelet Transform (MFC framework))

一篇关于小波变换和希尔伯特变换的文章，处理的是无功功率。小波变换代码和希尔伯特变化代码(A Wavelet transform and Hilbert transform article, dealing with reactive power.Wavelet transform and Hilbert transform code)

语音信号去噪，在MATLAB开发环境下，对含噪声的语音信号进行小波变换，根据阈值去噪的原理去噪，然后逆变换得到增强的语音信号(Speech Signal Denoising in the MATLAB development environment, including noise on the voice signal wavelet transform, in accordance with the principle of threshold denoising Denoising, and then inverse transform enhanced speech signal)

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.)

java小波变换的实现，包括哈尔小波，以及在这基础上改进的小波实现。(The implementation of Daubechies wavelets.)

小波变换的MATLAB源程序，使用语语音增强，去除噪声效果好，算法实现简单，清晰(MATLAB source wavelet transform, using language speech enhancement, noise removal effect, algorithm is simple and clear)