rdasgvfc

Implementation of a parks Macleland filter in Matlab and HDL

处理二维红外数据的代码,可以直接导入数据进行计算（.m)(For 2D FTIR，Easy to use)

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.

随机信号分析，包括随机信号的数字特征，相关函数和协方差，带图形显示。(Random signal analysis, including the number of characteristics of random signals, correlation functions and covariance, with graphical display.)

压缩感知雷达信号处理matlab仿真实验，可对目标场景建模及回波信号处理有一个总体的认识。(A simulation for compressive sensing radar singal processing based matlab.)

非线性拟合,用于非线性拟合时，可以用这个现成的代码，很发方便！(Nonlinear fitting for nonlinear fitting, you can use the existing code, it is made ​ ​ easy!)

DEMO_COND demonstrates the role of the condition number of a matrix (with respect to inversion) in the role of linear system solving. Matthias Heinkenschloss Department of Computational and Applied Mathematics Rice University Feb 22, 2001

利用传递矩阵计算转子系统的临界转速 很实用的 (critical speed)

GLOTLF Liljencrants-Fant glottal model U=(D,T,P)

matlab的基本操作，适用于初学者，个人总结，以及网上摘录。(the basic use of matlab，adapt for newer)