543 search results - page 13 / 109 » Nonlinear principal component analysis of noisy data |
CORR
2010
Springer
13 years 7 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 ...
BMCBI
2006
13 years 7 months ago
2006
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
KDD
2006
ACM
14 years 8 months ago
2006
ACM
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
NC
2007
13 years 7 months ago
2007
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is de�...
ISNN
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best r...