neural network design books matching source (Matlab platforms)

最大概率分词法,这种分词算法能够较好的解决汉语分词中的歧义问题,但分词效率比最大匹配分词算法要低-greatest probability points accidence, Segmentation algorithm can be used to solve the Chinese word segmentation of Ambiguity, but Word efficient than the largest matching segmentation algorithm lower

人工智能的过程表示法求解九宫问题,vc开发-artificial intelligence to the process that method JiuGongTu, vc Development

一个用C编写的SOM（自组织特征映射）神经网络源代码。-a C prepared by the SOM (self-organizing feature map) neural network source code.

7。《进化算法》，云庆夏编着 冶金工业出版社 2000年第一版 全书共分5章，分别为绪论、遗传算法、遗传规划、进化策略、进化规划。-7. "Evolutionary algorithm," Yun Qing Xia compile Metallurgical Industry Publishing House in 2000 the first edition of the book is divided into five chapters, each of the introduction, Genetic algorithms, genetic programming, evolutionary strategy, evolutionary programming.

汉语分词系统，对中文语句进行识别，然后分词，是很好的自然语言理解的例子-Chinese word segmentation system, the Chinese phrase for identification, then Word, is a very good natural language understanding examples

来自于www2.cs.uregina.ca的c4.5源码-from the Bank www2.cs.uregina.ca FOSS

神经网络与matlab实现,内含大量的实例,希望能对你有所帮助.-neural network and Matlab realized, with a lot of examples and I hope that you can help.

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

利用PSO优化SVM，利用分组式训练方法提高算法速度-PSO to optimize the use of SVM, the use of packet-style training methods improve algorithm speed