Matlab-R14-brief-introduction

八皇后问题，用matlab解决八皇后问题，以及多皇后问题，采用追溯法(Eight queens problem)

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. )

说明：  use for research in the image processing techniques in medical image processing

用MATLAB计算大摆角单摆的实验报告，希望对大家有帮助。(simple pendulum)

说明：  多线性主成分分析的MATLAB源代码 最初用于人脸识别和步态识别 后被扩展到其他应用领域(The codes implement two algorithms: Multilinear Principal Component Analysis (MPCA) and MPCA+LDA.)

PSCAD 中调用MATLAB进行计算或仿真 例程(PSCAD call MATLAB for calculation or simulation routines)

PCA特征提取代码,对图像进行识别，并输出识别率，附详细说明(PCA characteristic extract code)

各种雷达信号处理的代码，全部都能用，有助于对雷达信号的学习。(A variety of radar signal processing code, all of them with the help of radar signals learning.)

struct2的一个列子，简单的描述了struct2的配置和测试使用(A Lie struct2 and simple description of the configuration and testing of the use of struct2)

是基于STBC的MIMO-OFDM的MATLAB仿真，生成误码率曲线(MATLAB simulation is based on the STBC MIMO-OFDM generate BER curves)