搜索资源列表
MFA
- MFA: Marginal Fisher Analysis
MFA
- Marginal Fisher Analysis算法，可用于降维，注释有使用说明！供大家学习交流！-Marginal Fisher Analysis algorithm, can be used for dimensionality reduction, the Notes are used to explain! For all to learn!
NFA-DFA-MFA
- 正则表达式及NFA-DFA-MFA的转换和判别-Regular expressions and NFA-DFA-MFA conversion and discriminant
selfadapting2
- 一个自适应控制方面的Simulink程序，主要解决无模型自适应（MFA）控制的问题-Adaptive control of a Simulink procedures, mainly to solve the model-free adaptive (MFA) control
selfadapting3
- 另一个解决无模型自适应控制问题的Simulink模型，可以作为学习MFA的参考 -Another solution to the issue of model-free adaptive control of the Simulink model can be used as reference for learning MFA
mfa_sy2
- 根据Yan et al. 文章编写的MFA程序，希望对大家有帮助；如果存在问题，也希望指正！-According to Yan et al. The article written MFA program you want to help If there are problems, but also want to correct me!
MFA
- 无模型自适应（MFA）控制 不需要精确模型，通过自适应算法控制。-MFA control
zhengze
- 正则表达式及nfa到dfa再到mfa的转化-Regular expressions and nfa to dfa conversion and then to mfa
mfa
- 混合因子分析器的EM算法及其VC++实现-EM for Mixtures of Factor Analyzers
mfa
- probability principle component analysis, using matlab to reduce the dimenission of data.
mfa
- mfa的源码，老外写的，很不错，需要时直接在相关文件中修改参数即可~-the code of mfa
BianYiYuanLi
- 编译原理所有重要算法的实现 以及词法分析语法分析、中间代吗生成。LL1 LR0 算符优先 算符表达式到NFA再到DFA的算法。-Compile program. LL1 LRO NFA->DFA->MFA
201010yueMFAkaoshi
- 2010十月联考MFA考试辅导--电影资料（靳斌老师9-23）-October 2010 exam MFA Prep- Movie (Jin Bin teacher 9-23)
mfa
- 用于盲信号分离的原代码，可以根据输入源信号的基本统计特征,由观测数据进行信号分离,最终恢复出源信号。 -Blind signal processing has become an emerging subject in signal processing in these years, which depends on the source signal statistical characteristics to separate the signals from the observa
MFA
- 边界fisher判别，用于人脸识别，在yale库取得比较好的效果-Boundary fisher discriminant for face recognition, in the library to obtain better results yale
MFA
- genel olarak c++ hersey
Compile
- 编译原理，词法分析器的实现，可以读取pasal文件，进行词法分析，实现DFA，NFA，MFA的转换-Compiler theory, lexical analyzer to achieve, you can read pasal file for lexical analysis, implementation DFA, NFA, MFA conversion
MFA
- 自己写的MFA降维算法。此算法中先进行pCA处理原始数据，然后对处理后数据运用MFA，可用于人脸识别及其它分类问题。很好用。-Write your own MFA dimensionality reduction algorithm. This algorithm first performed pCA processing raw data, processed data and then use MFA, can be used for face recognition and other
NFA-DFA-MFA
- 编译原理中从正规式转换到NFA,之后NFA-DFA-MFA三者之间的转换，支持打开文件与保存文件-Compile the transition formal to NFA, and then convert between NFA-DFA-MFA to support opening files and saving files
MFA 边缘Fisher分析
- MFA 边缘Fisher分析 降维算法，是基于LDA的改进