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使用DCT和小波变换的数字音频水印生成/解码程序，可存活于方差0.05的高斯白噪声及不同程度的剪切。内含程序/测试文件介绍。(Digital wartermarking encoding/decoding program with DCT and wavelet transform. nice robustness against Gaussian noise with variance less than 0.05 and any type of cropping attack. functions/test files introduction included)

利用小波变换实现表面肌电信号消噪的程序，还包括一些对比分析。(Wavelet transform SEMG denoising procedures, including some comparative analysis.)

关于小波变换的一些常用函数，有关多尺度变换，希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)

用于时频分析，其中包括短时傅里叶变换、小波变换、脊线提取以及一些信号的生成等。(For time-frequency analysis, including short-time Fourier transform, wavelet transform, ridge extraction and generate some signals and so on.)

基于MATLAB的GS算法的高斯光束整形设计(Designof BinaryOptical Element withMATLAB)

用小波神经网络变换对时间序列信号进行预测，并做了测试，效果很好，请参考(Transform using wavelet neural network to predict the time series signal, and do a test with good results, please refer to)

基于小波变换的信号去噪技术，简单的一维小波去噪程序(Signal de-noising based on wavelet transform technique, a simple one-dimensional wavelet denoising procedure)

matlab利用小波模极大值法实现信号的奇异性检测(Signal singularity detection in Matlab)

小波方法进行降噪，阈值函数来完成不同设计，核心程序如下面的所示，使用的小波基有coif5，db3，sym4，bior2.4，haar，rbio(Wavelet method for noise reduction, design to complete different threshold function, the core program as shown below, using the wavelet base coif5, db3, sym4, bior2.4, haar, rbio )

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.)