Neural Network Based Speech Recognition Technology based on neural network speec...

人工神经网络的c++实现源码,含实现神经网络层的类,神经网络的类,中文详细注释, 并含有使用示例,学习神经网络的好源码-Artificial neural network c++ implementation source code, including achieve the type of neural network layer, the type of neural network, a detailed English notes, and contain the use of examples of good learning neural network source code

遗传算法（C++版），非常好的！-genetic algorithm (C version), very good!

（其中已经包含5个源码）所附源程序C或C++代码文件及其可执行文件 Scs.cpp 基本分类算法源程序， 输入数据文件cfile.txt,efile.txt,gfile.txt,pfile.txt ,rfile.txt,tfile.txt Sga.c 基本遗传算法源程序, 输入数据文件input，输出文件output A_life.c 基于遗传算法的人工生命模拟源程序, 输入数据文件world GA_nn.c 基于遗传算法优化神经网络结构源程序,输入数据文件sample Patmat.c 基于遗传算法提取基元图形源程序-(which includes five OSS) attached to C or C source code files and executable files Scs.c pp basic classification algorithm source files, input data files cfile.txt, efile.txt. gfile.txt, pfile.txt, rfile.txt. tfile.txt Sga.c basic genetic algorithm source files, input data files input, output file output A_life.c based on genetic algorithm simulation source Artificial Life, import data files GA_nn.c world based on genetic algorithm optimization neural network structure source, import data files Patmat.c sample extraction based on genetic algorithm-based graphic source yuan

模式识别分类程序，贝叶斯，神经网络分类训练程序，很不错啊-the classification procedures, Bayesian neural network classifier training procedures, and it is very responds :

由 Visual C++ 编译过，可以求解任何个数城市的tsp问题，只要输入城市坐标即可。-By Visual C++ Compiled, you can to solve any number of cities tsp, so long as you enter the city coordinates.

greedy em 混和模型训练算法-greedy em hybrid model training algorithm

采用MFC技术，实现蚁群算法和遗传算法，形象化了算法实现的过程，有助于我们的学习和理解。-Use of MFC technology to realize ant colony algorithm and genetic algorithm, visualization of the algorithm implementation process, contribute to our learning and understanding.

粒子群算法的示例程序，不错。可用来进行函数优化、神经网络训练等。-PSO algorithm sample program, yes. Available for function optimization, neural network training.

This directory contains code implementing the K-means algorithm. Source codemay be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANSprogram accepts input consisting of vectors and calculates the givennumber of cluster centers using the K-means algorithm. Output isdirected to the screen.

BPMLL is a package for training multi-label BP neural networks. The package includes the MATLAB code of the algorithm BP-MLL, which is designed to deal with multi-label learning. It is in particular useful when a real-world object is associated with multiple labels simultaneously