3D-strange-attractor

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.

This document is common informantion for hardware development to measuringer temperature with TC

车牌自动识别代码，附图 车牌自动识别代码，附图(Base image license plate Identification Base image license plate Identification)

2级倒立摆模型，matlab仿真,需要的可以看一下(2_daolibai code)

AR随机过程的建模，给定一个AR过程，对其进行建模，分别利用Yule-Walker方程和协方差法进行功率谱估计(AR random process modeling, given an AR process, its modeling, respectively, Yule-Walker equations and covariance method of power spectrum estimation)

计算分段三次多项式插值的系数,计算三次样条插值函数的系数组M(Calculating the coefficients of piecewise cubic polynomial interpolation, cubic spline interpolation function calculating the coefficients M)

matlab and visual c++ program method and explaination

详细的介绍了UKF算法在matlab中的实现过程，并有matlab测试例子，适合UKF初学者(Described in detail in the UKF algorithm in matlab implementation process, and matlab test case for beginners UKF)

对仿真信号进行特征值分解，进行奇异值降噪处理(SVD Denoise)

说明：  基于倒谱法的基音周期检测，有着不错的参考意义。(The pitch period detection based on cepstrum method has a good reference value.)