genetic-algorithm

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. )

层次聚类算法 MATLAB实现，没有调用函数(Hierarchical clustering algorithm based on MATLAB realize, do not call the function)

bit error rate for Binary phase shift keying

基于matlab编写的自适应遗传算法算例(Prepared based on adaptive genetic algorithm matlab example)

估计Hilbert矩阵的2条件数和矩阵的阶数的关系用Gauss消去，分别用Gauss消去，Jacobi迭代，Gauss-seidel迭代，SOR迭代和共轭梯度法求解，比较结果。(Discuss the 2 condition number of the matrix and the matrix order relations.Using different methods like Gauss，Jacobi，Gauss-seidel，SOR and GS)

高阶谱分析，很实用，能帮助分析非平稳信号(Higher order spectral analysis, it is useful to help analyze non-stationary signals)

this is a program for measuring instantaneous angular speed from pulse signal. this file contents source code for instantaneous angular speed estimation.

用matlab 编写的 ，目标做匀速和匀加速运动，使用强跟踪对其进行滤波(Prepared using matlab, goals do uniform and uniformly accelerated motion, the use of strong tracking filter them)

合成孔径雷达(SAR)点目标数据模拟生成的matlab程序(Matlab program for SAR simulation data generation)

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