CPN算法的matlab实现，CPN人工神经网络

用的VC6编的可以识别联机数字，联机英文，及联机汉字-the VC6 series of the figures can be identified on-line, on-line English, and Chinese characters on-line

随机神经网络的源代码，对于研究神经网络的人来说，可能有一定的参考作用-random neural network source code for research neural network people, may have some reference

回溯法求01背包问题,c语言版本，由于时间关系没有将代码进行很好的整理，所有代码都在一个文件中-Retrospective Method 01 knapsack problem, c language versions, due to time not finishing a very good code, all code in one file

这是一个自动走迷宫的寻路算法。 可能会有人需要，用作游戏的。 自己新建个Win32空项目，把这个代码复制进去就行了。-This is a Maze of automatic routing algorithm. Some people would argue the need for the game. In their new empty Win32 project, copy this code into there.

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.

一个bp实现回归的nn程序，可以从中学习神经网络在回归中的应用-Bp realize a return nn procedures, neural networks can learn from the reunification of the application

k-means(欧氏距离)聚类算法是最基本的聚类算法，是理解和应用聚类算法的基础，通过k-means(欧氏距离)聚类算法我们才可以初步了解数据挖掘的原理。-k-means (Euclidean distance) clustering algorithm is the most basic clustering algorithm, is understanding and the basis for the application of clustering algorithm, through the k-means (Euclidean distance) clustering algorithm we are able to a preliminary understanding of the principles of data mining .

不错的自组织神经网络算法，程序有注释。能运行，效果还行。-good self-organizing neural network algorithm, the procedure Notes. Can run, the results were OK.

神经网络的算法，关于BP网络的编写-neural network algorithm, on the preparation of BP Network

CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation