搜索资源列表
001
- 基于pca和dpca以及流形法的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedu
002
- 基于pca和dpca以及流形法和动态流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method and dynamic manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good e
00
- 基于pca和kpca以及流形法和核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method and procedure of the nuclear manifold hair, applied to fault detection and fault diagnosis, and fault recognition, identification of the go
0
- 基于kpca以及核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and nuclear manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedure is
000
- 基于kpca以及dpca,核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and dpca, nuclear manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, pr
01
- 基于kpca以及pca,核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and pca, nuclear manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, proc
02
- 基于kpca以及pca,dpca,流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and pca, dpca, manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, pr
03
- 基于kpca以及pca,pls,流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and pca, PLS, manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, proc
05
- 基于kpca以及pca,dpls流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and pca, DPLS manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, proc
11
- 基于pca,dpls流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca, DPLS manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedure is si
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- 基于pca,dpls流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为csth，程序简单-Based on the pca, DPLS manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object is the CSTH, procedure is
isomap
- 流形学习的经典短发 ISOMAP 的原代码-classical algorithm of isomap, it is quite useful in manifold learning
suwenjunExpressionRecognition
- 用流形算法来进行人脸表情的识别，该实验是基于matlab平台来进行的仿真实验，-With the manifold algorithm for facial expression recognition, the experiment is based on matlab platform for simulation experiments
LLE
- 流行学习法代码，非常好用~~~赶快下载吧-The code of manifold learning ,very useful~~
Space-Reconstruction
- 流行学习法中要用的相空间重构，非常好用，谢谢使用-Space reconstruction in the method of manifold learning
manifoldlearning
- 流型学习的matlab demo，包含了8种算法和9个实例-In the last few years, many manifold learning techniques have been developed for Non-Linear Dimensionality Reduction (NLDR). To my knowledge, no one has surveyed the techniques to determine which method performs the best
manifold_learning
- 包含流形学习主要经典算法的matlab源程序，用来探索和研究manifold learning相关问题。-source codes for manifold learning researches.
KLPP
- 这是一个kernel lpp流行学习算法（Kernel Locality Preserving Projections），-Kernel Locality Preserving Projections for manifold usingmatlab
mani
- 流形学习的经典算法，包括有:PCA,MDS,ISOMAP,LLE,Hessian LLE,LTSA, Laplacian,Diffusion Map-The classic manifold learning algorithm, including: PCA, MDS, ISOMAP, LLE, Hessian LLE, LTSA, Laplacian, Diffusion Map
MFA_code_doc
- 基于流形学习的压缩感知，程序设计的基本流程框架-manifold of Compressive Sensing,