the C language, BP artificial intelligence algorithms can be seen teaching

基于matlab的指纹识别系统，采用基于细节点对比，输入图像必须是256×256，8－bit灰度值，500dip的指纹。-Matlab-based fingerprint identification system based on Minutiae contrast, imported images must be 256 x 256.8-bit gray scale values 500dip fingerprints.

数据挖掘经典算法遗传算法的C++实现源码-Classical data mining algorithm for genetic algorithm C++ Realize source

各种神经网络C源代码。包括： CPN、BPN、ART1、ART2。-various neural network C source code. Include : CPN, 7.82, ART1, ART2.

关联规则中的频繁项集生成算法genmax，可在linux和windows下编译运行，可能不太容易看懂。-association rules of frequent item sets genmax generation algorithm, and the Linux compiler running under windows, it may not be easy to understand.

基本的BP神经网络框架，比较适用于初学者快速掌握神经网络的构成。-basic framework BP neural network, suitable for beginners to grasp the composition of neural networks.

求解函数最大值的遗传算法Matlab源代码-maximum function for the genetic algorithm source code Matlab

遗传算法神经网络，遗传算法神经网络遗传算法神经网络-genetic algorithm neural networks, genetic algorithms neural networks, genetic algorithm, neural network

经过改进的遗传算法的VC源代码。经测试算法有效可行。-improved genetic algorithms VC source. Testing Algorithm effective.

基于自组织特征映射网络的聚类分析，是在神经网络基础上发展起来的一种新的非监督聚类方法，分析了基于自 组织特征映射网络聚类的学习过程，分析了权系数自组织过程中邻域函数和学习步长的一般取值问题，给出了基于自组织 特征映射网络聚类实现的具体算法，并通过实际示例测试，证实了算法的正确性。 -Based on self-organizing feature map network cluster analysis, neural network is developed on the basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm.

首先采用某种编码方式将解空间映射到编码空间，每个编码对应问题的一个解，称为染色体或个体。一般通过随机方法确定起始的一群个体，称为种群，在种群中根据适应值或某种竞争机制选择个体，使用各种遗传操作算子产生下一代如此进化下去，直到满足期望的终止条件。-begin using some form of coding mapping to the solution space coding space, each encoding a corresponding solution to the problem, known as chromosome or individual. General randomly determined by the initial group of individuals, called stocks, the stocks based on fitness or some mechanism to choose the individual competition, the use of genetic Operator evolution of the next generation so on, until the termination meet expectations conditions.