Short communication: Automated, rapid classification of signals using locally linear embedding

Authors:
J. M. Nichols;F. Bucholtz;B. Nousain
Affiliations:
Naval Research Laboratory, 4555 Overlook Ave., SW, Washington, DC 20375, United States;Naval Research Laboratory, 4555 Overlook Ave., SW, Washington, DC 20375, United States;Naval Research Laboratory, 4555 Overlook Ave., SW, Washington, DC 20375, United States
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

This paper demonstrates the utility of the locally linear embedding (LLE) dimensionality reduction technique for automated, rapid classification of signals. Specifically, we focus on classifying RF signals as belonging to one of four different emitters. The classifier is trained on samples from each type, first using LLE to build a low-dimensional data manifold and using a support vector machine (SVM) to divide the manifold into sections corresponding to each signal type. New signals are then rapidly projected directly onto the data manifold where an SVM performs the classification.