The use of neural networks, basis of comparison, more useful for beginners

apriori算法是数据挖掘的经典算法之1,其基于关联规则的思想.这是我的第2个收藏算法-algorithm is data mining algorithms of a classic algorithms, based on the idea of association rules. This is my first two collections Algorithm

本程序实现通过构造一棵前缀树实现 最大模式频繁项集挖掘算法.应用fp树增长算法实现.-the program by constructing a prefix tree to achieve the greatest model Frequent Mining algorithms. Application fp growth tree algorithm.

mtlab的遗传算法的源程序,很好用的,这是个压缩文件,请解压缩后使用-mtlab genetic algorithm source, the good, it is a compressed file, decompress after use

自适应共振理论（ART）-Adaptive Resonance Theory (ART)

单神经元pid源码实现，对初学的朋友很有帮助-The program can realize single neural pid with MATLAB.The algorithm is simple and easy to understand.

3个径向基网络的matlab源程序[matlab],一维输入，一维输出，逼近效果很好！-three RBF network Matlab source [Matlab], one-dimensional input and one-dimensional output. Approximation good effect!

一个高人的VC实现NN的程序。很不错。先运行Matrixbase.dsw,again arithmetic.dsw, next nnbp.dsw,final neuralNetWork.dsw.-an expert in VC NN procedures. Very good. First running Matrixbase.dsw, again arithmetic.dsw. next nnbp.dsw, final neuralNetWork.dsw.

这是一个神经网络开发包。目录ann下是专门针对神经网络的代码，外部目录是一些公用的代码，与神经网络无关，但是神经网络的代码用到了它们。 ann目录下有一个目录demo，里面存放了一些示例程序，请参照它们进行编程。 ann/prj/vs7下是编译整个库的Visual Stdudio 2003工程文件-This a neural network development kit. Ann directory under specific neural network code, external directory is some common code, has nothing to do with the neural network, but neural networks use of their code. Ann directory is a directory demo, stored inside a sample program, please refer to their program. Ann/prj/vs7 under compiler for the entire 2003 Visual Stdudio engineering documents

模糊算法，实现了求交法计算模糊蕴含关系、最大最小法进行合成运算、求并法计算输出量的模糊集合、加权平均法计算实际的清晰控制量等部分的详细代码。-Fuzzy algorithm, the realization of the intersection method to calculate fuzzy implication relations, max-min method for synthesis of computing, and method for output fuzzy sets, the weighted average method to calculate the actual volume of clear control of part of the detailed code.

1、编制程序显示印章图像（24位真彩色位图）； 2、读出位图中每一像素点的（R，G，B）样本值； 3、以RGB其中某两个（或三个）为坐标，取一定数量的图像点为分析样本，分析其坐标系中的分布； 4、采用本章学习的方法找到分类判别函数，对这些样本进行分类；（要求首先将印章与底纹区分，如有可能将印章、底纹、签字区分） 5、将分类后的结果标记到原始图像上，检查其效果。 -1, the preparation procedures showed that the seal image (24-bit true color bitmap) 2, read out each bitmap pixel (R, G, B) sample value 3 to RGB which a two (or three ) for the coordinates, take a certain number of image points for the analysis of samples, analysis of its coordinate system of distribution 4, the method used in this chapter to learn to find discriminant function classification of these samples for classification (required first to distinguish between the seal and Shading, if possible, will seal, Shading, signatures to distinguish between) 5, will be the result of classification markings to the original image to check its effectiveness.