搜索资源列表
Fisher
- Fisher判别，用于模式识别的Fisher线性判别-Fisher Discriminant for pattern recognition Fisher Linear Discriminant
stprtool1.0
- 该工具箱是用于统计模式识别的，运行于matlab环境中。用户可以根据需要自行修改-The toolkit is used for statistical pattern recognition, operating in the Matlab environment. Users may need to amend its own
ALGER
- 使用C++编写的经典数值计算算法,包括NEWTON迭带法,SIMPSON,二分法,二分法求根,还附加了模式识别的FISHER算法-prepared to use the classic C numerical algorithms including Netwon Diez belt law, Simpson, black, black roots, also added a pattern recognition algorithm Fisher
20060712003
- 一种汉字模式识别的VC++源代码，里面包含了学习与识别的算法实现，识别一种汉字前，先学习几遍。识别率高，对学习与研究模式识别很有好处。方便修改。-a Chinese character pattern recognition VC source code, which contains the learning and recognition algorithm, a Chinese character recognition, first learn several times. The hi
gendata
- 用于模式识别的MATLAB源代码,准确性高,比较好用.
kmean
- 用于模式识别的MATLAB源代码,准确性高,比较好用.
knn
- 用于模式识别的MATLAB源代码,准确性高,比较好用.
pazzern
- 用于模式识别的MATLAB源代码,准确性高,比较好用.
tree
- 用于模式识别的MATLAB源代码,准确性高,比较好用.
Cjunzhi
- 模式识别的C均值聚类算法,用C语言编写的,可运行
PROJECT
- 这是我们 模式识别的project,识别手写数字，准确率很高
patternrecognition
- 模式识别的vc程序包括模板匹配神经网络识别
BP
- BP神经网络用于函数拟合与模式识别的Matlab示例程序
ycsj
- 遗传算法用于函数拟合与模式识别的Matlab示例程序
BP-moshi
- BP神经网络用于函数拟合与模式识别的Matlab示例程序,说明很详细,并且代码可以直接拿来用-BP neural network for function fitting and pattern recognition procedures Matlab examples to illustrate in great detail, and the code can be directly used by
K_average
- 简单的模式识别的分类算法（K_均值算法）-Simple pattern recognition algorithm (K_ means algorithm)
Visual_Cppshuzituxiangmoshishibie
- Visual C++数字图像模式识别技术及工程实践_光盘源码 极其有价值-Visual C++ Digital image pattern recognition technology and engineering practice is extremely valuable source _ CD-ROM
shiyan_moshi
- 模式识别的 图像的贝叶斯分类 图像的贝叶斯分类 神经网络模式识别-Bayesian pattern recognition image classification image of the Bayesian classifier neural network pattern recognition
targetrec
- 图像模式识别算法， 很不错的ＶＣ＋＋源码．．． 请大家使用-Image pattern recognition algorithms, it is a good VC++ source code. . . Please use the
基于BP神经网络的函数拟合与模式识别的Matlab程序
- 基于BP神经网络的函数拟合与模式识别的matlai代码(Function Fitting and Pattern Recognition Based on BP Neural Network)