algorithm data mining algorithm is the classic algorithm, which is based on the...

基于神经网络的字母识别系统 -Letters based on neural network recognition system

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

一个神经网络原型代码，针对的例子为《Perceptron Learning》 (Russell & Norvig， 第742页)-A neural network prototype code, for example for

网络能通过学习带正确答案的实例集自动提取“合理的”求解规则，即具有自学习能力-network can learn the correct answer with examples of automatic drawing of the "reasonable" solution rules, that is self-learning ability

一个简单的遗传算法C++类-a simple genetic algorithm C

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.

我收集整理的有关于系统辨识的资料和一些方法的优缺点-I have collated the information on the system identification and the advantages and disadvantages of some methods

使用最小二乘支持向量机对多维pyrim数据进行回归，需要下载最小二乘支持向量机工具箱。-use of least squares support vector machines for multidimensional data pyrim return need to download least squares support vector machines toolbox.

遗传算法，通过选择、交叉、变异求取函数最优解c程序简单实现，并拥有最优保存思想。-Genetic algorithm, selection, crossover and mutation to strike a function of the optimal solution c procedures are simple to achieve, and has saved the best idea.

这是一个关于目前最前沿课题的神经网络学习模型的程序-xor-This is a topic on the forefront of the current neural network learning procedures for model-xor