神经网络模式识别及其实现，第三章。为大家提供参考。

前馈神经网络算法-feed forward neural network algorithm

基于神经网络的电离层F2层临界频率预测方法 基于神经网络的电离层F2层临界频率预测方法-Based on neural network of ionospheric layer F2 critical frequency forecasting methods based on neural network of ionospheric layer F2 critical frequency forecasting methods

是国外相关研究人员提供的发现频繁模式（包括频繁集、频繁子图等）的最新版本算法。-Foreign researchers with the relevant frequent pattern discovery (including frequent itemsets, frequent subgraph, etc.) the latest version of algorithm.

MATLAB 下的模式识别特征提取 用于对特征信号的提取-MATLAB under the feature extraction for pattern recognition features of the signal extraction

提供了遗传算法的一些代码库文件，国外下的很有用-provide the genetic algorithm code of the document, the foreign useful

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.

针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。 -against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.

基于点轨迹的手势识别.鼠标右键点击开始记录鼠标轨迹,基于记录的轨迹,利用神经网络算法进行识别.-Trajectory based on the point of gesture recognition. By right-clicking the mouse to start recording the track, based on track record, the use of neural network algorithm to identify.

用于求解多目标优化问题，多目标进化算法源程序-The code for multi-objective optimization algorithm

数据挖掘中的关联规则发现算法-Data Mining Association Rules algorithm