它是一个基于遗传算法的优化方法，使用微分运算符。它用于解决带有大量未知事物的优化问题。...

神经网络C程序的第9章-neural network C procedures for the Chapter 9

基于SVM，分本分类，，是关于两类分类的比较好的工具，国外网站提供，效果很好的-based SVM, the sub-classification is on the classification of the two types of relatively good tool, overseas sites provide good results, the

决策树分类中经典算法的ID3和Ｃ４．５代码公共包！-Classical decision tree classification algorithm ID3 and C4.5 code public packet!

蚂蚁算法在服务质量方面的代码，主要是服务质量方面的东西-Ant Algorithm in the service quality of the code, mainly the quality of services of things

给出了FIR滤波器设计的C语言程序，可以根据设计要求，灵活地调整参数，得到需要的滤波器参数。-given FIR filter design in C language program, according to the design requirements, flexibility to adjust parameters and the filter parameters.

一个用VC++开发的采用模糊C均值聚类算法.-a VC development of the fuzzy c-means clustering algorithm.

自已用C++写的手势辨识,可分出四个不同的手势。-Themselves with C++ Written gesture recognition, can be the separation of four different gestures.

LM编程算法，在神经网络中有很大应用之处，神经网络源代码,及BP网络训练界面,其中的L-M算法非常实用 -LM programming algorithm, in a large neural network applications, the neural network source code, and the BP network training interface, in which the LM algorithm is very practical

GENNET是一个通过遗传算法优化权重的16个神经元的全连接神经网络。训练目的是使网络在一定假设的激励下，随时间产生同目标函数同样的响应，即:可以把此网络制作为一个任意波形的信号发生器。 程序分3个示例说明遗传算法进化过程中网络输出的变化趋势。可以看出网络输出（蓝色曲线）随着时间变化逐渐逼近目标函数（红色曲线）。此程序不仅可以学习遗传算法，也可以用于研究全连接网络的直观示例。-GENNET is a genetic algorithm to optimize the weights by the 16 neurons fully connected neural networks. Training purposes is to enable network inspired by certain assumptions, over time, produce the same response with the objective function, namely: the network can be produced as an arbitrary waveform signal generator. Procedure, three examples illustrate the evolution of genetic algorithms in the network output trends. We can see that the network output (blue curve) changes over time, gradually approaching the objective function (red curve). This program can not only learn from the genetic algorithm can also be used to study visual example of a fully connected network.

非线性程序之模式识别与控制系统设计.-nonlinear pattern recognition procedures and control system design.