one we are looking for the em algorithm, achieving Matlab

经典的K均值分类算法源码，修正了原作者没有处理当类中样本为0的情况下的bug-classic K-mean classification algorithm source code, that the original author did not address when the category 0 samples of the bug

机器人运动学正解程序,毕业设计可用,希望能有点用场-robical code ，i hope it can be useful for you

我的八数码游戏！！ 学人工智能的编写的-my eight digital game! ! The study prepared by the Artificial Intelligence

对于学习混沌理论的人很有用的，这也是搜集到的-Chaos Theory for the study were very useful, which is collected

利用最大匹配法进行汉语句子的分词 最大匹配算法是最常用的分词算法，简单实用正确率可达到80%以上-the maximum matching method for the Chinese Sentence Word maximum matching algorithm is the most commonly used word segmentation algorithm, simple and practical accuracy rate can reach more than 80%

基于GA的BP改进算法，用遗传算法对BP 神经网络算法进行改进试用过 里面有数据是可以使用的-GA-based improvement of BP algorithm, genetic algorithm with BP neural network algorithm tried there are data that can be used

基于C开发的三个隐层神经网络，输出权值、阈值文件，训练样本文件，提供如下函数：1）初始化权、阈值子程序；2）第m个学习样本输入子程序；3）第m个样本教师信号子程序；4）隐层各单元输入、输出值子程序；5）输出层各单元输入、输出值子程序；6）输出层至隐层的一般化误差子程序；7）隐层至输入层的一般化误差子程序；8）输出层至第三隐层的权值调整、输出层阈值调整计算子程序；9）第三隐层至第二隐层的权值调整、第三隐层阈值调整计算子程序；10）第二隐层至第一隐层的权值调整、第二隐层阈值调整计算子程序；11）第一隐层至输入层的权值调整、第一隐层阈值调整计算子程序；12）N个样本的全局误差计算子程序。-C development based on the three hidden layer neural network, the output weights, threshold documents, training sample documents, for the following functions : a) initialization, the threshold subroutine; 2) m learning samples imported subroutine; 3) m samples teachers signal Subroutine ; 4) hidden layer of the module input and output value subroutine; 5) the output layer of the module input and output value subroutine; 6) the output layer to the hidden layer subroutine error of generalization; 7) hidden layer to the input layer subroutine error of generalization; 8) the output layer to the third hidden layer Weight adjustment, the output layer threshold adjustment routines; 9) 3rd hidden layer t

经典的BNP神经网络例子-classic example BNP neural network

在人工智能中模式识别比较新的分类算法,支持向量机.用于特征分类.-A new classify arithmetic of pattern-recognition in artificial intelligence,use support vecotr machine to classify the characteristic

中科院的《高级人工智能》课件，希望对大家学习有帮助。-Chinese Academy of Sciences