326 search results - page 1 / 66 » Principal Component Analysis for Distributed Data Sets with ... |
110
Voted
APPT
2005
Springer
15 years 6 months ago
2005
Springer
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
101
Voted
ICIP
2002
IEEE
16 years 2 months ago
2002
IEEE
This paper is organized as follows. In Section 2, we formulate the proposed UMPC method for modeling nonstationary and multi-modal data. Both MPC and UPC are shown to be special ca...
108
Voted
CORR
2010
Springer
15 years 1 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 ...
115
Voted
GLOBECOM
2009
IEEE
15 years 7 months ago
2009
IEEE
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
99
Voted
CORR
2010
Springer
15 years 1 months ago
2010
Springer
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...