资源列表
NeNMF_code
- 非负矩阵分解的最新算法的matlab实现，以及多种算法之间的对比，和在图像识别中的应用,实测可用-The latest non-negative matrix factorization algorithm matlab implementation, as well as the contrast between a variety of algorithms and image recognition applications, the measured available
GA
- 这是一个博士论文，关于遗传算法的论文，是智能控制学习的好资料，请大家分享！-This is a Doctor thesis,Genetic Algorithms Intelligent Control of materia
Mathematical-modelingamatlab
- 给文件包含了几乎所有数学建模用到的分析法，如模糊数学，神经网络，灰色模型，并包含有相关模型matlab代码，可作为建模竞赛培训材料。-To the file contains almost all of the mathematical modeling used in the analysis, such as fuzzy, neural network, the gray model and includes the relevant model matlab code can be use
javascript
- javascr ipt网页制作及毕业论文带源代码-javascr ipt web production and thesis with source code
6
- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之八十八-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, diagnosis rate is ninety-nine percent, and the fault recognition rate is eigh
6
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十三-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
6
- The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate is sixty-seven perce-The program use pca, kpca, SVM, PLS, fisher, bayesian r
Digitale Signalverarbeitung: Bausteine, Systeme, Anwendungen _Chapter 5 Sourcecode
- Sourcecode for Chapter 5 of Digitale Signalverarbeitung: Bausteine, Systeme, Anwendungen
prtools
- SVDD（无监督）分类器中所用到的程序集-SVDD classifier used in the assembly
SVMs1
- 基于支持向量机的CPI走势与影响因素分析-Based on Support Vector Machine CPI trend and influencing factors
Huffman
- 利用huffman编码原理进行文件的压缩与解压-Huffman coding principle the use of compression and decompression file
SVM
- 支持向量机的一些文献，对学习支持向量机的同学很有用哦-The literature on support vector machines, support vector machine learning is useful for students oh