C realized SVM neural network code, welcome you use

遗传算法方法，步骤，实例。详细，有实例，很不错。-Genetic algorithm methods, steps, examples. Detail, there are examples of very good.

开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.

神经网络模拟正弦函数演示-neural network simulation sine function demo

基于Hopfield人工神经网路的室内全域路径优化。主要是利用Hopfield求解TSP的方法。用于课程设计。-based on artificial neural network Hopfield indoor entire domain path optimization. Hopfield is mainly used for TSP method. For course design.

基于MATLAB的神经网络非线性系统辨识软件包.-MATLAB-based nonlinear neural network system identification package.

离散二进制粒子群算法 DPSO -DPSO

蚂蚁算法，c语言版，其中，‘F’点表示食物，‘H’表示窝，白色块表示障碍物，‘+’就是蚂蚁了。-Ant algorithm, c language version, of which,

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.

人工智能模式识别中基于非负矩阵分解生成特征空间的算法-artificial intelligence pattern recognition based on non-negative matrix factorization generation features of the algorithm space

A星算法实现最短路径的选择,使用方便，功能完善，是学习人工智能作业中必须完成的一步。-Choose the shortest path by the method of AStar