Extracted-from-the-ECG-signal-

说明：  本书是关于小波变换和MATLAB的应用的相关书籍，从这本书可以了解到如何利用MATLAB实现小波变换。(This book is about the application of wavelet transform and MATLAB related books, this book can learn how to use MATLAB implementation of wavelet transform.)

基于小波变换的通信信号码元速率估计.pdf(Estimated rate based on the communication signal element wavelet transform. Pdf)

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)

对于非平稳信号，小波多尺度分解师一种有效的信号去噪方法，在小波去噪方法的基础上，提出了基于Lipschitz指数的小波阈值去噪方法(For non-stationary signals, signal de-noising of wavelet multi-scale decomposition ' is an effective method, wavelet denoising method based on proposed wavelet thresholding denoising method based on the Lipschitz exponent)

数字基带传输基带信号，指未经调制的信号。这些信号的特征是其频谱从零频或很低频率开始，占据较宽的频带。 基带信号在传输前，必须经过一些处理或者某些变换（如码型变换、波形和频谱变换）才能送入信道中传输。处理或变换的目的是使信号的特性与信道的传输特性相匹配。 数字基带信号是消息代码的波形表示。表示形式有多种，有单极性、双极性波形，归零和非归零波形，差分波形、多电平波形之分，各自有不同的特点。 研究数字基带信号通过加性高斯白噪声信道的传输，并且假设信道除了叠加高斯噪声外，不会对信号产生其他失真。(matlabSimulation(pulse amplitude modulation) modulation signal in AWGN (additive white Gaussian noise AWGN (Additive White Gaussian Noise)) under the channel bit error rate and bit error rate performance, and compared with the theoretical value.)

curvelet变换最新工具包，含有快速离散曲波变换的所有形式（包括基于usfft和wrapping和3dfdct）。功能强大，是学习曲波变换的好帮手。(curvelet transform the latest kit, containing the fast discrete curvelet transform all forms (including those based on usfft and wrapping and 3dfdct). Powerful learning curvelet transform is a good helper.)

vc实现虚拟示波器，没有测试过不知道能用吧(vc virtual oscilloscope not tested do not know can)

中值滤波源程序，非常好用。程序有说明很容易看懂！(median filtering source, very handy. Note procedure is easy to read!)

高斯滤波.这段代码主要用于以为信号的高斯滤波。(Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter)

双树复小波变换的源代码，可用于一维信号与二维图像的变换(double-tree Complex Wavelet transform the source code can be used in one-dimensional and two-dimensional image signal transformation)