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Scalable Wideband Principal Component Analysis via Microwave Photonics

Author(s): Ferreira De Lima, T; Tait, AN; Nahmias, MA; Shastri, BJ; Prucnal, Paul R

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dc.contributor.authorFerreira De Lima, T-
dc.contributor.authorTait, AN-
dc.contributor.authorNahmias, MA-
dc.contributor.authorShastri, BJ-
dc.contributor.authorPrucnal, Paul R-
dc.date.accessioned2020-04-01T13:23:14Z-
dc.date.available2020-04-01T13:23:14Z-
dc.date.issued2016-3-4en_US
dc.identifier.citationFerreira De Lima, T, Tait, AN, Nahmias, MA, Shastri, BJ, Prucnal, PR. (2016). Scalable Wideband Principal Component Analysis via Microwave Photonics. IEEE Photonics Journal, 8 (10.1109/JPHOT.2016.2538759en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr17r44-
dc.description.abstractMicrowave photonics (MWP) provides advantages in bandwidth performance and fan-in scalability that are far superior to electronic counterparts. Processing of many channels at high bandwidths is not easily achievable in any electronic implementation. We consider an MWP system that iteratively performs principal component analysis (PCA) on partially correlated, eight-channel, and 13-GBd signals. The system that is presented is able to adapt to oscillations in interchannel correlations and follow changing principal components. Wideband multidimensional techniques are relevant to > 10-GHz radio systems and could bring solutions for intelligent radio communications and information sensing.en_US
dc.language.isoen_USen_US
dc.relation.ispartofIEEE Photonics Journalen_US
dc.rightsFinal published version. This is an open access article.en_US
dc.titleScalable Wideband Principal Component Analysis via Microwave Photonicsen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1109/JPHOT.2016.2538759-
dc.date.eissued2016-3-4en_US
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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