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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http://arks.princeton.edu/ark:/88435/pr17r44| Abstract: | Microwave 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. |
| Publication Date: | 4-Mar-2016 |
| Electronic Publication Date: | 4-Mar-2016 |
| Citation: | Ferreira 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.2016.2538759 |
| DOI: | doi:10.1109/JPHOT.2016.2538759 |
| Type of Material: | Journal Article |
| Journal/Proceeding Title: | IEEE Photonics Journal |
| Version: | Final published version. This is an open access article. |
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