1051 search results - page 4 / 211 » An algorithm for the principal component analysis of large d... |
ICRA
1998
IEEE
14 years 6 days ago
1998
IEEE
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
SDM
2011
SIAM
12 years 10 months ago
2011
SIAM
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
IJCNN
2000
IEEE
14 years 10 days ago
2000
IEEE
Fuzzy c-varieties (FCV) is one of the clustering algorithms in which the prototypes are multi-dimensional linear varieties. The linear varieties are represented by some local prin...
CORR
2010
Springer
13 years 8 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
CVPR
2003
IEEE
14 years 10 months ago
2003
IEEE
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...