psd_cal

说明：   这是一个用小波神经网络进行非线性函数逼近的例子，拟合效果非常好，保证能运行！有详细注释！我是参考《青岛海洋大学学报》 2001年第1期 一种基于BP算法学习的小波神经网络编写的，大家可以针对原文更好的理解我的程序！(This is a wavelet neural network with nonlinear function approximation example of fitting results is very good, guaranteed to run! Detailed Notes! I refer to Journal of Ocean University of Qingdao，2001 ，“a learning algorithm based on BP wavelet neural network ”, you will understand me better for program!)

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)

基于小波变换的数字盲水印及对嵌入水印后图像的攻击检测(Attack detection based on wavelet transform digital blind watermark and the watermarked image)

小波去噪,通过对含噪信号进行四层小波分解，此处利用db3小波系列，通过仿真发现可以很好的消除信号中的噪声(Wavelet denoising, the signal through four layers of noisy wavelet decomposition, where the use db3 wavelet series, the simulation found in the well to eliminate the noise signal)

用小波变换和OMP重构的压缩感知算法来重构lena图像。(CS Algorithm with DWT and OMP。)

二次小波变换的方法用于数字信号码元速率估计(wavelet transform for bitrate estimation of digital modulated signal)

说明：  python实现小波和短时傅里叶变换，源代码和测试算例(Python implementation of wavelet and short time Fourier transform)

双树复数小波变换的滤波程序,在所有小波变换的程序中，该程序采用双变量模型能很好完成去噪功能(dual-tree complex wavlet transform is a good inshift wavelet transform)

小波阈值去噪 软阈值去噪和硬阈值去噪的比较(Wavelet thresholding soft thresholding and hard thresholding comparison)

数字信号处理的c++库，很好的资源，作者很牛，包括数值计算与常用的信号处理分析,例如FFT、小波变换、功率谱估计等(Digital Signal Processing c++ library, a great resource,including numerical analysis and common signal processing，such as FFT, wavelet transform, power spectrum estimation)