- DCODEANDENCODE 字符串加密解密！算法很简单！抛砖引玉之用！请不要扔板砖！
- brain 神 经 网 络 的 资 料
- STL.zip source code from Mastering The Standard C++ Classes using C++. 1) The source code listings from each chapter can be found in the listings directory. The listings directory is divided by chapter. 2) A html quick reference for the most commonly used C++ classes can be found in the html directory. To use this html reference use your browser to select the \html directory. Open the file named index.htm
- m_seq 利用MATLAB实现的产生M序列的程序及自动产生本原多项式的程序
- 128bitCLA 128位CLA 采用kogge
- mvc5sheep 基于MVC的C++五子棋游戏源码
资源列表
outstar
- matlab写的简单的联想网络实例，模拟dog,meat,light生物条件反射实验-matlab write simple examples of the association network, analog dog, meat, light on Biological conditioned reflex experiments
NeuralNet
- neural network code, this writre for student tha can learn basic neural nework
RLS_RBF
- 基于递归最小二乘的神经网络算法程序，基于matlab-A rls-rbf
RBF
- RBF源程序，调试好了的，可以为神经网络的学习提供帮助-RBF code
BP
- 一层BP神经网络逼近函数，用MATLAB编写，不是神经网络工具箱。-Layer BP neural network approximation function, prepared using MATLAB neural network toolbox.
FNNjieousuanfa
- 给出了一模糊神经网络解耦控制算法,对含有噪声的二阶系统进行控制,并与PID控制结果进行了比较,效果不错!-Given a fuzzy neural network decoupling control algorithm, controls the second-order system for noise control and PID control and the results were compared with the effect of good!
floodfill
- 种子染色法（USACO）逼人的较复杂解法-Seed stain (USACO) pressing the more complex solution
Ssvmmsmooe
- 支持向量机smo算法，，非常好的实现ＳＶＭ的算法 -Smo algorithm, support vector machine, very good implementation of SVM algorithm
NN
- 这个仿真是在时滞投影神经网络的基础之上进行的改进网络，用来解决二次规划问题。-This simulation is based on the time-delay neural networks projection carried improve network for solving quadratic programming problems.
竞争网络聚类
- 神经网络中的竞争网络聚类-neural network competition in the network clustering
rbf_nn
- 類神經網路的RBF這對於任何研究都非常之友幫助歡迎下載內有說明-The RBF neural network for any research to help the Friends are welcome to download, there are notes
FLch6eg2
- 采用基于遗传算法的神经网络学习非线性函数。目标函数为：yp=1-exp(-i/2).-Genetic algorithm-based neural network learning of nonlinear functions. The objective function as: yp = 1-exp (-i/2).