搜索资源列表
mpc85xx_mds
- MPC85xx MDS board specific routines.
mds-progress4-dated-28-02-13
- this file contains the code about content based image retri
llog
- OST<->MDS recovery logging infrastructure.
SVM
- This code just simply run the SVM on the example data set heart_scale , which is scaled properly. The code divides the data into 2 parts train: 1 to 200 test: 201:270 Then plot the results vs their true class. In order to visualize the h
mds_client
- mds reply parsing for Linux v2.13.6.
RankTest
- 搜索分组密码扩散层MDS矩阵 主要搜索8bit S盒 分组为32的分组密码-search the MDS matrix if not, got the almost perfect matrix
lustre_eacl
- MDS data structures. See also lustre_idl.h for wire formats of requests.
mdc_lib
- packing of MDS records for Linux v2.13.6.
llog_net
- MDS recovery logging infrastructure.
mpc837x_mds
- MPC837x MDS board specific routines.
mpc832x_mds
- Descr iption: MPC832xE MDS board specific routines.
usb-phy
- Unfortunately, we have to lie to MDC MDS to retrieve attributes llite needs and provideproper locking.
mpc836x_mds
- Descr iption: MPC8360E MDS board specific routines.
mpc834x_mds
- MPC834x MDS board specific routines.
taskstats-struct
- mds unlink log: the MDS adds an entry upon delete.
Isomap
- ISOMAP(Isometric Feature Mapping，等度规特征映射)算法在高维非线性数据处理中有较为理想的效果，建立在MDS (Multi-Dimensional Scaling，多维尺度变换)的基础上，其基本思想是当数据集的分布具有低维嵌入流形结构时，可以通过保距映射获得观测空间数据集在低维空间的表示。-ISOMAP (Isometric Feature Mapping, and other metric feature mapping) algorithm can get mo
drtoolbox.tar
- 用于降维的matlab工具包，包括PCA，LDA，LLE，等-Matlab Toolbox for Dimensionality Reduction Principal Component Analysis (PCA) Probabilistic PCA Factor Analysis (FA) Classical multidimensional scaling (MDS) Sammon mapping Linear Discriminant Analysis (LDA
Dimension-reduction-tools
- 这是一个人机交互界面，里面包含了PCA、MDS、流形学习等一些算法供大家使用-This is a human-computer interaction interface, contains the some algorithms such as PCA, MDS, manifold learning for all to use
mani
- 此代码是关于流形学习，数据降维，代码中含有的主要方法是PCA，KPCA，MDS，KMDS，Laplacian等等，且代码作了可视化处理，界面效果完美-This code is on the manifold learning, data dimensionality reduction, the main method code is contained in PCA, KPCA, MDS, KMDS, Laplacian, etc., and the code visualization ma
Localization
- 多种不基于测距的定位算法比较，包括APIT、DV-hop、Bounding Box、MDS-MAP等等 注释清晰-Ranging is not based on a variety of localization algorithm comparison, including APIT, DV-hop, Bounding Box, MDS-MAP, etc. Note clear