Computer Engineering Commons^™

Canonical Correlation Feature Selection For Sensors With Overlapping Bands: Theory And Application, Biliana S. Paskaleva, Majeed M. Hayat, Zhipeng Wang, J. Scott Tyo, Sanjay Krishna

Electrical and Computer Engineering Faculty Research and Publications

The main focus of this paper is a rigorous development and validation of a novel canonical correlation feature- selection (CCFS) algorithm that is particularly well suited for spectral sensors with overlapping and noisy bands. The proposed approach combines a generalized canonical correlation analysis framework and a minimum mean-square-error criterion for the selection of feature subspaces. The latter induces ranking of the best linear combinations of the noisy overlapping bands and, in doing so, guarantees a minimal generalized distance between the centers of classes and their respective reconstructions in the space spanned by sensor bands. To demonstrate the efficacy and the …