Information Measures for Multisensor Systems
Memorandum rept. Jan-Apr 2013
NAVY TECHNOLOGY CENTER FOR SAFETY AND SURVIVABILITY WASHINGTON DC
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The purpose of this report is to demonstrate the utility of an information-theoretic approach to next generation chemical detection. Recent research at the Naval Research Laboratory NRL has yielded probabilistic models for spectral data that enable the computation of information measures such as entropy and divergence, with the goal of developing feature sets to increase the sensitivity and selectivity of multivariate chemical sensors of several modalities. Results are presented for several types of spectral data in multisensor systems, as well as strategies for using information measures with other data sources. Binary, univariate, and multivariate sensors can all be modeled from an information-theoretic perspective, making it well-suited for the challenges of next generation chemical detection.
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