开发环境:C语言 简要说明:BackProp算法：BP网络是反向传播(Back Propagation)网络。它是一种多层前向网络，采用最小均方差学习方式。这是一种最广泛应用的网络。它可用于语言综合，识别和自适应控制等用途。BP网络需有教师训练。
标签： Propagation BackProp Back 网络
上传时间： 2013-12-28
上传用户：liuchee
BackProp算法：经典的B-P算法.
上传时间： 2014-11-22
上传用户：xc216
神经网络模式识别及其实现，第四章。 内含：ALOPEX和BackProp程序。
上传时间： 2013-12-09
上传用户：363186
神经网络源程序代码，有常用的BackProp算法,行程编码算法RCL,动态聚类算法,LVQ(学习矢量量化)算法等等，自己看吧
上传时间： 2015-05-21
上传用户：xiaoyunyun
JaNet: Java Neural Network Toolkit resume: A well documented toolkit for designing and training, and a java library for inclusion in third party programs. description: jaNet package is a java neural network toolkit, which you can use to design, test, train and optimize an ideal Neural Network for your private application. You can then include your saved network in your program using the jaNet.BackProp package. The consequent documentation is only in french for the moment, but an english translation is planned. The java source code is released under GPL, and can be compiled with JDK, Symantec Cafe or MS Visual J
标签： documented designing training Network
上传时间： 2016-04-15
上传用户：zhanditian
The code on this diskette has been organized by chapter. Each subdirectory containing listing has a readme.txt describing program usage and any relevent file formats. The readme will also describe how to compile the target programs under IBM OS/2 (TM) using the using C Set++ compiler (TM). All programs on this diskette have been compiled and tested in this environment. The majority of programs on this diskette should port to other environments with only minor adjustments. The exception to this are those programs which utilize presentation manager for graphical display of program data. In particular, the grid1 programs in \chapt4\BackProp\ and \chapt3\ fall into this latter category.
标签： subdirectory containing has organized
上传时间： 2016-10-28
上传用户：冇尾飞铊
