SimDataAnalysis

粒子追踪测速的相关程序，所使用的算法为最邻近原则，通过粒子链表形成匹配(Particle tracking velocimetry procedures, the algorithm used for the nearest neighbor principle formed by particles linked list match)

此文件中有部分内容，对于初学MATLAB的人有帮助，前俩部分是一些MATLAB的基础操作，第三部分是线性方程数值解的雅克比迭代和高斯—赛德尔迭代的例子，第四部分是Gauss-Legendre积分公式，Newton-Cotes积分公式的俩个数值积分的例子，第五部分是Euler公式、向后Euler公式、改进Euler公式，二阶Runge-Kutta等方法（微分方程数值解）。(The first two parts are basic operations of MATLAB. The third part is examples of Jacobian iteration and Gauss-Seidel iteration of numerical solution of linear equation. The fourth part is examples of Gauss-Legendre integral formula and Newton-Cotes integral formula. The fifth part is Euler formula, backward Euler formula, improved Euler formula, second-order Runge-Kutta method (numerical solution of differential equation).)

用MATLAB实现dpsk信号调制，载波信号(Using MATLAB to achieve dpsk signal modulation, the carrier signal)

PCA MATLAB 实现人脸识别的程序 (PCA MATLAB realize face recognition process)

调用程序可对信号进行EMD分解，再进行奇异值分解降噪(The calling program can decompose the signal by EMD, then the singular value decomposition and denoising 2D empirical wavelet program. The calling subroutine can perform the empirical wavelet transform on the image.)

Particle swarm optimization in wireless sensor networks

k近邻选取，在降维的时候需要构造邻接矩阵，需要选取近邻的个数(k neighborhood selection)

iterative learning control simulink

Multiscale Block Compressed Sensing with Smoothed Projected Landweber Reconstruction

这个Matlab程序实现最速下降算法。最速下降法是一种最基本的算法，它在最优化方法中占有重要地位.最速下降法的优点是工作量小，存储储变量较少,初始点要求不高；缺点是收敛慢，最速下降法适用于寻优过程的前期迭代或作为间插步骤，当接近极值点时，宜选用别种收敛快的算法. (The Matlab program to achieve the steepest descent algorithm. Steepest descent method is a basic algorithm, it occupies an important position in the optimization method. Advantage of the steepest descent method is the small amount of work, less storage reservoir variables, the initial point less demanding drawback is slow convergence, the steepest descent method for the optimization process of the early iterations, or as inserted steps are advised to use other kinds of fast convergence of the algorithm when close to the extreme point.)