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这里是一些VC与matlab混合编程的最新技术资料。有些是介绍了在VC ++调用Matlab的常用方法及各自特点，还有一些是介绍VC与matlab混合编程的实例。(Here are some VC mixed with matlab programming information on the latest technologies. Some are introduced in VC++ calling Matlab common methods and their own characteristics, and some is to introduce the VC with the matlab programming examples of mixing.)

说明：  生成分形和混沌的matlab程序包括Julia集和Mandelbrot集。操作简单有效。(Program for generating fractals through Iterated Function System (IFS) and Chaos Game. This program has also the possibility to read IFS from file. Moreover it draws Julia Sets and Mandelbrot Set. The usage is simple. Just type "fractals" and then the main window appears.)

these codes are about simulation of vcsel laser diod

denoise In BayesShrink[5] we determine the threshold for each subband assuming a Generalized Gaussian Distribution(GGD) . The GGD is given by GG¾ X ¯ (x) = C(¾ X ¯ )exp¡ [® (¾ X ¯ )jxj]¯ (6) ¡ 1 < x < 1 ¯ > 0, where ® (¾ X ¯ ) = ¾ ¡ 1 X [ ¡ (3=¯ ) ¡ (1=¯ ) ]1=2 and C(¾ X ¯ ) = ¯ ¢ ® (¾ X ¯ ) 2¡ ( 1 ¯ ) and ¡ (t) = R1 0 e¡ uut¡ 1du. The parameter ¾ X is the standard deviation and ¯ is the shape parameter It has been observed[5] that with a shape parameter ¯ ranging from 0.5 to 1, we can describe the the distribution of coefficients in a subband for a large set of natural images.Assuming such a distribution for the wavelet coefficients, we empirically estimate ¯ and ¾ X for each subband and try to find the threshold T which minimizes the Bayesian Risk, i.e, the expected value of the mean square error.

each bank has this offset apart from the 1 2 bank that is mixed into the other 3 ranges.

matlab生成随机数，uinform产生一组[0，1]分布的随机数，riddling产生一个N(0,1)正态分布随机数，normal产生n个N(a,b)正态分布随机数。(Use matlab to generate random numbers, uinform produce a set of [0,1] random number distribution, riddling produce a N (0,1) normally distributed random numbers, normal generate n N (a, b) normally distributed random numbers.)

in this file is distribution-system

矩形检测,基于MATLAB的利用霍夫变换，自己弄的，很实用(rectangular detection)

This implementation of progressbar is intended to be extremely simple to use while providing a high quality user experience. Features: - Can add progressbar to existing m-files with a single line of code. - Supports multiple bars in one figure to show progress of nested loops. - Optional labels on bars.

AMRA 模型 修改的Yule_walker方法( modified Yule_walker method for AMRA )