autorun

是自适应阈值的分割，主要对图像用matlab进行分割图像，确定图像想要的东西(Adaptive segmentation threshold, the main image to image segmentation using matlab, determine what image you want)

matlab hann hamming window FFT DFT DTFT

调试所用Matlab版本是6.5，gatbx-toolbox是调试过程中使用的工具箱，有些热心的研友已经提供了该工具箱，之所以再贴一遍，是因为6.5版本下调试该工具箱会出现一些错误提示，在该版本中已经进行了改正，使用该工具箱只需要将压缩包下的gatbx和gatbxTest_fns加入到Matlab搜索路径即可，另外gatbx-origin是Sheffield大学提供的原始版本的工具箱，未做任何改动，两者可做比较之用 3.gatbx-example是算例调试源码和各算例的调试说明，大家可以对照原书进行比较 4.窃以为gatbx工具箱较之Matlab7新版下的gads工具箱更能让人熟悉和了解遗传算法的原理和计算过程，虽然在可视化方面不及gads 5.学习遗传算法如果首先用熟相关工具箱的话，能够先培养信心，然后更有兴趣去专研和了解具体的算法，如果就用现有的工具箱就能解决问题的话，不了解其详细的算法也未尝不可，毕竟不是每个研友都能向see_moonlight那样开发自己的工具箱吧, ( The debugging uses the Matlab edition is 6.5, gatbx-toolbox debugs the toolbox which in the process uses, somewhat warm-hearted ground the friend already to provide this toolbox, the reason that pasted again, was because under 6.5 editions debugged this toolbox to be able to present some wrong prompts, had already carried on the correction in this edition, will use this toolbox only to need to compress package of under gatbx and gatbx Test_fns joins to the Matlab search path then, moreover gatbx-origin was the primitive edition toolbox which the Sheffield university provided, has not made any modification, both might make the comparison are the example debugging sound code and various examples debugging explained with 3.gatbx-example, everybody might compare the original bookCarries on comparison 4. in my opinion under the gatbx toolbox s to be able to let the human compared with Matlab7 update gads toolbox be familiar with the understanding genetic algorithm principle and)

Matlab教程第六章案例，时间序列分析与计量(Matlab Guide Chapter cases, time series analysis and measurement)

求混沌时间序列的广义维(genealized dimension) (Seeking generalized dimensional chaotic time series (genealized dimension))

本文的程序实现在屏幕上随机产生不同大小的雪花，并以不同的速度下降。相对于第一版，它在很多性能上做了优化，直接在桌面的上下文中绘制雪花。而且，现在也通过RedrawWindow，实现在桌面的图标(如任务栏)上绘制雪花了。你可以用它来学习GDI。(Falling Snow on Your Desktop! Part II This article explains how to create an application that makes it snow on the desktop. Since my previous article was published, I received many user inquiries about how to improve the program. This article demonstrates how to create snow flakes that fall on your desktop, by using the draw functions directly in the desktop context. When the application starts, it creates an array of snow flakes and starts the timers for each flake. Manipulation of the RedrawWindow function allows the drawing of flakes behind and over the desktop icons, making the application more impressive. )

基于小波变换的分开—合并图像分割matlab．采用多尺度小波变换系数作为四分树结构的分开一合并法图像分割的一致性度量 从而在大的图像块中。。去除噪声的影响，在小的图像块中，以小波变换的局部极大值精确定位边缘，根据边缘信息进行分开一合并法图像分割 ．实验表明．算法得到满意的结果 ． (Separately based on wavelet transform- merge image segmentation Matlab. Multi-scale wavelet transform coefficients as the quadtree structure separate consolidation method of image segmentation consistency measure large image block. . To remove the effects of noise, in small image blocks, the local maxima of the wavelet transform precise positioning edge, to separate a combined method for image segmentation according to the edge information. Experiments show. Algorithm to obtain satisfactory results.)

Matlab中erf(x)函数的表达式是怎样的，erf(x)与标准正态分布函数之间的关系是怎样的，怎样自己编制一个计算标准正态分布函数数值近似值的函数，如何利用matlab自带的erf(x)函数包近似计算标准正态分布函数的值，数值计算值与用erf(x)转化求得的值之间的相对误差是怎样的。(将中文译成英语 Matlab, erf (x) function expression is what, erf (x) the standard normal distribution function and the relationship between what and how to prepare their own calculation of the standard normal distribution function a value function approximation, how to use matlab comes with erf (x) function package approximate standard normal distribution function values??, numerical values ??and with erf (x) between the values ??obtained into the relative error is like. )

说明：  此程序是用vc做的喷泉模拟实验 产生数据在砸爱matlab中画图就可以得到了(This procedure is done fountain vc simulation generated data in matlab hit love in drawing can be a)

说明：  三种子波函数，sinc函数 正弦函数 Riker函数还有有限差分介质设定(Third seed wave function, sinc function, sine function has finite difference Riker media set)