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详细介绍了matlab程序设计方法，并给出了具体例子，有助于大家理解编程(it introduces matlab design method, and gives the specific examples,can help everyone understand the programming )

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. )

卡尔曼滤波原文，详尽解释了卡尔曼滤波器的由来和推导过程(Kalman original, elaborate ideas and derivation of Kalman Filter)

matlab图像分割识别算法。读入车牌可识别出车牌号码并输出。(matlab image segment algorithm. read in a car license plate can output the number in the plate.)

机载雷达空时自适应处理的源码,也就是林肯实验室的ward报告(Code for space-time adaptive processing foe airborne radar(J.Ward report of Lincoln Lab))

实现地震叠前三参数反演（纵波速度、横波速度、密度）(prestack seismic inversion (compressional wave velocity, shear wave velocity, density))

MATLAB 很经典的案例分析，和 matlab 神经网络30个案例分析配套

圆孔及方形孔的forunhofer 衍射示例(GS matlab )

卡尔曼滤波方面的matlab代码集，好不容易收集来的，供大家使用(matlab code for kalman filter)

利用CTD测量的压力、温度、电导率数据，获得盐度、声速、密度。(Derive slainity, sound velocity and densinity CTD data.)