stft

1.OFDM入门零基础，及其宝贵和重要的仿真建模文档。 2.通过实例将OFDM在通信系统中的各种特性描述出来。 3.文档中含有该场景下所有仿真的源代码(文档的附录最后面)，已在matlab下全部编译通过。(1.OFDM entry zero-based, and its valuable and important documents simulation modeling. 2. By example in the OFDM communication system describe the various features. 3. A document that contains all the simulation under this scenario the source code (appendix to the final surface of the document), has been under the full compile matlab.)

说明：   此函数用于研究Mallet算法及滤波器设计 此函数用于消噪处理 分解的高频系数采用db9较好,即它的消失矩较大 分解的有用信号小波高频系数基本趋于零 对于噪声信号高频分解系数很大，便于阈值消噪处理(this function for research Mallet filter algorithm design and function for Denoising decomposition of high-frequency coefficients Terminal better that it's vanishing moments larger decomposition of useful signal, high-frequency coefficients tends to zero for high-frequency signal noise decomposition coefficient great ease threshold Denoising)

Matlab code to obtain MAC address or physical Address of PC

光谱数据预处理程序，包括MSC,SNV,归一化，中心化，导数等等(Spectral data preprocessing procedures, including MSC, SNV, normalization, centering, etc. derivative)

物理下行信道的加扰，加扰子模块，需要自己设定参数，即可运行(Physical downlink scrambling, scrambling module, need to set parameters, you can run it )

matlab 图像处理pdf文件 包含许多MATLAB图像处理函数(MATLAB image)

将有的数据间隔大于10s的PKI数据与均匀10s的PRD数据整合成一个间隔<=10s的数据文件(Some data interval greater than 10s of the the PKI data with uniform 10s of the PRD data integration into an interval < = 10s data file)

kernel-ica package is a Matlab program that implements the Kernel ICA algorithm for independent component analysis (ICA). The Kernel ICA algorithm is based on the minimization of a contrast function based on kernel ideas.

Iterative learning neural network control for nonlinear system trajectory tracking

说明：  matlab科学计算继续上传，一共10个章节，由浅入深，几乎包括了绝大部分的科学计算方法以及仿真。本人把部分算法做了优化，更为完善(matlab scientific computing continue to upload a total of 10 chapters, easy-to-digest, almost, including most of the scientific method of calculation and simulation. I have done a part of algorithm optimization, a more perfect)