模糊规则库的实现

模糊技术与神经网络技术选编-fuzzy and neural network technology Selected

三维人脸动画的合成：利用数据挖掘和语音驱动（解决了语音和动画的同步）-3D Facial Animation Synthesis : Using Data Mining and voice-driven (to solve the voice and animation simultaneously)

是一个非常全面的pso的程序，有16个函数的测试，并且用三维图形将寻优过程显示出来。对所有的参数都可以修改测试-Is a very comprehensive procedure for the PSO, there are 16 function testing, and using three-dimensional graphics optimization process will be displayed. For all the parameters can modify the test

提出了基于最小化估计的泛化误差界非优化估计方法。目前大多数的核参数选择方法都是通过极小化了来得到最优参数值，但是求解优化问题的计算代价相当的大，并且不能很好地体现数据的分布特征。本文采用非优化技术，通过极小化泛化误差来优化核及相关参数，由于直接计算最小半径和最大间隔，避免了对优化问题的直接求解，因此可以很好地降低计算代价。并且该方法直接从样本出发，可以很好地体现数据的分布特征，不管数据分布是否均匀都可以适用。给出了基于凸包估计的SVM核选择的模型及实现算法。 -Proposed based on minimizing the estimated generalization error bound of the non-optimal estimation method. Most of the nuclear parameter selection methods are to get the best by minimizing the parameter values, but the computational cost for solving optimization problems is quite large, and can not properly reflect the distribution characteristics of the data. In this paper, the non-optimization technology, by minimizing the generalization error to optimize the nuclear and related parameters, due to the direct calculation of the minimum radius and maximum interval, avoiding the direct solution of the optimization problem, it can very well reduce the computation cost. And that the method directly from the sample one can well reflect the distribution chara

人工免疫网络,实现分类,聚类,函数寻优等功能,采用matlab编写.-artificial immune network, classification, clustering, search function Excellence function, prepared using Matlab.

本程序是用c语言编写的基于决策树分类方法的数据挖掘算法，它对测试集进行分类，挖掘出潜在的规则-this procedure is used to prepare the language c decision tree classification based on the data mining algorithm, which tests set for classification, tapping the potential rules

可视化的手写（鼠标）字母数字神经网络训练程序。-visulized neural network trainning programme。

神经网络C语言源程序-neural network C language source

该程序可以对二维三类样本进行分类，并画出分界面．学习过模式识别的人必看．要学习神经网络的人必看，代码简单，实用性强-the procedure three samples of two-dimensional classification and paint interface. Learning the pattern recognition Watchable. To study the neural network Watchable, code simple, practical

特别是在题库管理模块中对自动组卷功能常用的算法（包括随机选取法、回溯试探法和遗传算法）进行了比较。对于较流行的验证码技术也给出了具体实现。-particularly in the examination management module to automatically making up the algorithm commonly used functions (including random selection method, Retrospective testing and genetic algorithm) were compared. For more popular authentication code technology has provided a concrete realization.