DWT_1D

计算第二代harr小波变换或者说是整数提升小波变换的源代码(Calculation of second-generation or harr wavelet transform is an integer lifting wavelet transform of the source code)

说明：  LeGall(5，3)小波滤波器，其计算复杂度小、存储开销低、压缩效率高，已被JPEG2000标准采用。提升小波实例c语言实现(Lifting Wavelet Example C Language Implementation)

说明：  用于求取小波包变换后小波系数的熵值，对初学者很有帮助(Used to obtain the wavelet coefficients after wavelet packet entropy, helpful for beginners)

基于小波变换模极大的多尺度图像边缘检测matlab源代码(based on wavelet transform modulus maxima of multiscale edge detection Matlab source code)

说明：  小波变换用于脑电信号处理，可以很好的对脑电信号进行时频分析(Wavelet transform for EEG signal processing, can be very good for time-frequency analysis of EEG)

C语言实现一维离散小波变换，通过mallat算法实现对一维信号的快速重构和分解。(C language implementation of a one-dimensional discrete wavelet transform, fast algorithm by mallat one-dimensional signal reconstruction and decomposition.)

小波变换应用，小波软阈值及硬阈值去噪算法及对此算法的改进算法。(Application of Wavelet Transform, wavelet soft threshold and hard threshold denoising algorithm and improved algorithm for this method.)

说明：  实现对离散信号的连续小波变换进行时频域分析，判断信号的稳定性(The continuous wavelet transform of the signal is analyzed in time and frequency domain)

基于Gabor小波变换和人工神经网络的人脸识别方法，matlab代码。(Based on the Gabor wavelet transform and artificial neural network methods for face recognition, matlab code.)

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.)