这是我自己编的从数据中自动提取模糊规则的程序,这个文件中包括了一个主程序和几个函数,能够自动提起模糊规则、合并优化模糊规则。...

如何在VB下实现BP神经网络的拓扑优化算法

基于遗传算法和神经网络的外星人游戏的vc＋＋实现的程序-based on genetic algorithms and neural networks alien game vc++ procedures

细胞自动机的，很好的-Cellular Automata and fine

MATLAB 下的模式识别特征提取 用于对特征信号的提取-MATLAB under the feature extraction for pattern recognition features of the signal extraction

神经网络中神经元线性模型的C语言实现源程序！-Neural network linear model neurons realize the C language source code!

基于C语言人工免疫源程序,包括二进制编码的简单遗传算法源程序，二进制编码的简单克隆选择算法源程序-Artificial Immune-based C language source code, including a simple binary-coded genetic algorithm source code, binary-coded clonal selection algorithm simple source

The purpose of this computer program is to allow the user to construct, train and test differenttypes of artificial neural networks. By implementing the concepts of templates, inheritance andderived classes from C++ object oriented programming, the necessity for declaring multiple largestructures and duplicate attributes is reduced. Utilizing dynamic binding and memory allocationafforded by C++, the user can choose to develop four separate types of neural networks:

一套图像处理程序,支持三种图像文件格式,我调试过了,很好用-Image processing programs for JPEG,GIF and PNG.I have compiled them, which is good for using.

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