该程序是汉字识别算法的c++代码，通过训练后对输入的汉字进行识别，从原理上了解汉字识别的方法和实现过程。...

该系统使用极其简便，即使 你对各种网络模型不是很深刻的了解，也可以很好的使用该系统。使用时， 你可以自己修改网络的各种参数，交互性较好，而且该系统通过大量的图示 及参数设置，可以让你了解每个应用实例实现的过程及详细步骤。-The system is extremely easy to use, even if you have to various network model is not very profound understanding can be a good use of the system. When used, you can change the network"s own parameters, interactive better, but the system through a lot of icon and parameter settings, so you can understand each application process and the realization of detailed steps.

使用clips解决4人限定时间过河问题。附带clips源代码。-use clips resolve four limit the time the river issues. Fringe clips source code.

落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据,为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。-charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research

采用C编写的BP神经网络一个程序，请提意见-with C BP prepared a neural network procedures, please comment

隐马尔科夫模型工具箱windows可执行版本，可以广泛应用于识别等领域-HMM Toolbox windows executable version can be widely applied in areas such as identification

介绍了神经 网络中的HOPFIELD算法的C语言实现.-Introduce a neural network algorithm HOPFIELD realize the C language.

遗传算法的一个源码集成，内有数个c语言文件-a genetic algorithm source integration, which contains several language documents c

《神经网络理论与MATLAB7实现》电子书，超星4.0格式。- Neural network theory and implementation MATLAB7 e-books, Chaoxing 4.0 format.

图像模式识别的聚类器设计，采用VC++实现，和分类器设计相对应。-the designation of image pattern recognation,VC++ is adopted, along with the sort ware designation

SVM分类器，由上海交通大学编写，软件使用方便、好用-SVM classifier, from the preparation of the Shanghai Jiaotong University, the software easy to use, handy