人工智能神经网络识别 人工智能神经网络识别

c语言神经网络程序包-neural network package

利用SOM（Self-Organization Map）数据聚类方法，包含点数据集的坐标，并以TChart分组为例进行说明。

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.

一种通过自组织竞争学习网络实现数据降维和可视化的单层神经网络模型。用此算法可以把输入空间的多维映射到低维的（一维或者二维）的离散网络上，并将保持相同性质的输入数据在映射到低维空间时的拓扑一致性。iris以及letter两个数据集进行分类-A competitive learning through self-organizing network for data dimensionality reduction and visualization of single-layer neural network model. Using this algorithm can be multi-dimensional input space is mapped to the low-dimensional (one-dimensional or two-dimensional) discrete network, and will remain the same as the nature of the input data is mapped to the low-dimensional space of topological consistency. iris as well as the letter the two data sets to classify

Bayes分类器应用于IRIS数据集的例子-An example of Bayes Classifier applied on IRIS Data Set

rhapsody in C++企业解决方案-rhapsody in C++ Enterprise Solutions

研究生课程机器人控制基础大作业 检测直线与曲线-Robot Control Technology-DetectStraightlineAndCurves use matlab

这是一个有关于模式识别中的isodata算法的matlab源码。 大家可以看看。有详细注释-on the isodata pattern recognition algorithm Matlab source. We can look at. Detailed Notes

《游戏编程中的人工智能技术》一书中123章源代码- Game programming in artificial intelligence technology, one source book, Chapter 123

an approximate SVM solver, useful for very large dataset.