GENNET is a genetic algorithm to optimize the weights by the 16 neurons fully co...

这是一本进化算法的电子书，很适合人工智能方面的人学习-This is an evolutionary algorithm e-book, it is suitable for artificial intelligence to learn

一种运算效率较高的遗传算法-a higher genetic algorithms

给语音加噪声的一个程序，可以给定需要加噪声的分贝数，程序会自动加载，选用的是随机白噪声。-Plus noise to the voice of a program, you can determine the needs to increase the number of decibels of noise, the program will automatically load, selected at random white noise.

用C撰写遗传基因法-C genes written law

基于CPN人工神经网络的例子，供大家交流-CPN-based artificial neural network example, for U.S. exchanges

 1、有9个工件图像，要求从本章讲授的特征提取方法中，选择3~5种提取工件特征并给出数字结果；链码为必选方法，给出数字结果和图形显示，做到链码和原图像的双向变换显示。（实验报告中应描述相应的特征提取方法并略述实现过程）  2、设计的界面中要具备功能：任选1个工件作为目标，以上述实现的特征提取方法识别该目标的工件类型（即序号），并显示该判别基准特征的数据。  3、有可能的话试用聚类、训练或其他方法对这些工件进行分类。 -err

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.

二维核密度估计算法.以及最优化计算核宽度。-bivarite kernel estimation

斯坦福大学人工智能课程讲义（cs121）stanford university artificial intelligence course lecture notes-stanford university artificial intelligence course lecture notes

神经网络程序设计，遗传算法-neural network programming, genetic algorithm