Digital-Signal-Processing

基于小波变换的ECG信号去噪系统设计,在信号采集时，身体的任一微小运动都会产生“基线漂移”，这是一种低频干扰，同时，由于肌电的存在又产生了高频的肌电噪声，由于空间电磁场的存在又使心电信号中混有50Hz的工频干扰。这些噪声不去除，就会影响下一步的信号处理。 综合运用数字信号处理的理论知识进行生物医学信号增强系统设计，实现ECG信号的去噪，从而加深对小波变换及其应用的理解，建立概念多分辨分析的概念，加深理解信号增强的原理、方法和步骤。本设计的主要内容是设计一个基于小波变换的ECG信号去噪系统，实现ECG信号的去噪。 (ECG signal denoising based on wavelet transform system design, signal acquisition, any small movement of the body will have a " baseline drift" , which is a low-frequency interference, while the high frequency due to the existence of the EMG muscle electrical noise due to the presence of electromagnetic field and the ECG signal mixed with a 50Hz power frequency interference. The noise is not removed, it will affect the next step in the signal processing. Use the theoretical knowledge of digital signal processing for biomedical signal enhancement system design to achieve the de-noising of ECG signal, so as to deepen understanding of the wavelet transform and its applications, to establish the concept of multi-resolution analysis of the concept, deepen the understanding of signal enhancement of the principle, the method and steps. The main elements of this design is the design of an ECG signal denoising based on wavelet transform denoising the ECG signals.)

基于小波变换的语音识别，内含毕业论文和摘要以及可执行源程序(Speech recognition based on wavelet transform, containing thesis and summary of executable source code)

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.)

基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

对于PCA ，LDA，BIC，EBGM都有很详细的代码。但是需要在LINUX下配置运行。不过代码较有参考价值。(For PCA, LDA, BIC, EBGM have a very detailed code. But the need to configure to run under LINUX. However, a more useful code.)

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))

利用小波变换进行改进阈值信号去噪 (Improvement threshold signal denoising using wavelet transform)

its c-wavelet transform

its c-wavelet transform

基于DB4 的小波变换，实现了小波的分解与重构，可根据实际需要修改阈值的选取方法(Based DB4 wavelet transform to achieve wavelet decomposition and reconstruction, according to the actual need to modify the threshold selection method)