BPSO

信号与系统 相关分析与卷积运算的试验报告上课写的(Signal related to the system analysis and convolution computing class written test report)

matlab 包括遗传算法等，包括交叉，变异等，包括计算的结果等。 ( Matlab bao kuo yi chuan suan fa deng bao kuo jiao cha bianyi deng bao kuo ji suan de jie guo deng )

dark channel defog 包含在一个文本文件中的两个matlab程序能够实现很好的图像清晰化功能(decrease haze)

利用VC和Matlab混合编程,Release文件夹下可直接运行，绘出2D和3D图形。并且可以在VC 6.0环境下调试，注意文件夹中的readme文档说明。(Using VC and Matlab to program, Release folder can be run directly, draw 2D and 3D graphics. And it can debugging in VC 6.0 environment, pay attention to the folder readme documentation.)

干涉相位滤波（均值、中值、圆周期）用于insar的三种不同滤波方法(Three different filtering methods for InSAR based on interferometric phase filtering (mean, median and circle period))

Ponomarev Fixed Structured Automata Matlab Code

参考文献《基于泰勒级数展开的蜂窝TDOA 定位算法》以及 《基于Chan氏算法和Taylor级数展开法的协同定位方法》对Taylor算法进行仿真；认定基站数目为5个；(The Talyor algorithm in the TDOA location based on the CDMA cell network)

implements the GOST 28147 OFB counter mode (GCTR).

equalizer response for channel F(Z)=-.2Z^2+.5Z^1+1+.5Z^-1-.2Z^-2 for zfl and tap=7,9,15

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. )