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Neural network based novelty filtering for signal detection enhancement

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3 Author(s)
Hanseok Ko ; US Naval Surface Warfare Center, Silver Spring, MD, USA ; Baran, R. ; Arozullah, M.

Discusses the analytical basis for designing an adaptive novelty filter (ANF) based on a multilayer feedforward neural network in order to enhance the detectability of weak, transient signals in the presence of comparatively high-level background noise or interference which has unknown, uncharacterized, or time-varying statistical properties. The ANF serves as a front end preprocessor to any device which performs signal detection, estimation or classification. The ideal ANF would selectively filter out the noise while passing the signal without attenuation or distortion. The conditions under which the novelty filtering effect is most pronounced are presented

Published in:

Circuits and Systems, 1992., Proceedings of the 35th Midwest Symposium on

Date of Conference:

9-12 Aug 1992

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