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Projections designs for compressive classification

Publication ,  Journal Article
Reboredo, H; Renna, F; Calderbank, R; Rodrigues, MRD
Published in: 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
December 1, 2013

This paper puts forth projections designs for compressive classification of Gaussian mixture models. In particular, we capitalize on the asymptotic characterization of the behavior of an (upper bound to the) misclassification probability associated with the optimal Maximum-A-Posteriori (MAP) classifier, which depends on quantities that are dual to the concepts of the diversity gain and coding gain in multi-antenna communications, to construct measurement designs that maximize the diversity-order of the measurement model. Numerical results demonstrate that the new measurement designs substantially outperform random measurements. Overall, the analysis and the designs cast geometrical insight about the mechanics of compressive classification problems. © 2013 IEEE.

Duke Scholars

Published In

2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

DOI

Publication Date

December 1, 2013

Start / End Page

1029 / 1032
 

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Reboredo, H., Renna, F., Calderbank, R., & Rodrigues, M. R. D. (2013). Projections designs for compressive classification. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, 1029–1032. https://doi.org/10.1109/GlobalSIP.2013.6737069
Reboredo, H., F. Renna, R. Calderbank, and M. R. D. Rodrigues. “Projections designs for compressive classification.” 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, December 1, 2013, 1029–32. https://doi.org/10.1109/GlobalSIP.2013.6737069.
Reboredo H, Renna F, Calderbank R, Rodrigues MRD. Projections designs for compressive classification. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings. 2013 Dec 1;1029–32.
Reboredo, H., et al. “Projections designs for compressive classification.” 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, Dec. 2013, pp. 1029–32. Scopus, doi:10.1109/GlobalSIP.2013.6737069.
Reboredo H, Renna F, Calderbank R, Rodrigues MRD. Projections designs for compressive classification. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings. 2013 Dec 1;1029–1032.

Published In

2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

DOI

Publication Date

December 1, 2013

Start / End Page

1029 / 1032