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ASPDAC
2009
ACM
164views Hardware» more  ASPDAC 2009»
16 years 16 days ago
Accounting for non-linear dependence using function driven component analysis
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Lerong Cheng, Puneet Gupta, Lei He
GLOBECOM
2009
IEEE
16 years 23 days ago
Data Acquisition through Joint Compressive Sensing and Principal Component Analysis
—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...
Riccardo Masiero, Giorgio Quer, Daniele Munaretto,...
BMCBI
2008
115views more  BMCBI 2008»
15 years 6 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
ICASSP
2009
IEEE
16 years 23 days ago
Using complex-valued ICA to efficiently combine radar polarimetric data for target detection
Target detection in sea clutter is a challenging problem in radar detection, specifically, when the Doppler return of the target and clutter are collocated. Polarization diverse ...
Mike Novey, Tülay Adali
CORR
2010
Springer
320views Education» more  CORR 2010»
15 years 6 months ago
An algorithm for the principal component analysis of large data sets
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnis...