Program-for-Cross-corelation

csa simulation sar systems

2个不同调制方式的MATLAB仿真程序，是QPSK和QAM的，都非常好(Two different modulation of the MATLAB simulation program is QPSK and QAM, are very good)

该程序将计算机视觉的目标跟踪问题转化为寻找稀疏矩阵的过程，将预先的得到的样本粒子与稀疏矩阵线性相乘得到目标(The program will target tracking in computer vision into the process of finding a sparse matrix, the sample will be obtained in advance of the particles multiplied with the goal of sparse linear)

matlab 计算发动机点火提前角的实验计算程序(Matlab, the advanced ignition Angle of experimental applications)

Decryption algorithm of caeser which generate all possible combinations

k means 聚类聚类聚类聚类聚类聚类聚类聚类聚类(k means)

Mann-Kendall突变检验的matlab程序，设置的置信度95 ，当然这个很容易自己调整(Mann-Kendall mutation test matlab program, set 95 confidence level, of course, this is very easy to make their own adjustments)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

EKF codes,很经典的程序，有需要的人可以下载(EKF GPS INS DR)

Elliptic Cylinder case Smatrix for Eshelby Function in MicroMechanics