Neural network based novelty filtering for signal detection enhancement

Hanseok Ko; Robert Baran; Mohammed Arozullah

doi:10.1109/MWSCAS.1992.271387

Neural network based novelty filtering for signal detection enhancement

Hanseok Ko, Robert Baran, Mohammed Arozullah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

This paper concerns the analytical basis for designing adaptive novelty filter (ANF), based on a multilayer feedforward neural network, 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 pre-processor 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.

Original language	English
Title of host publication	1992 Proceedings of the 35th Midwest Symposium on Circuits and Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	252-255
Number of pages	4
ISBN (Electronic)	0780305108
DOIs	https://doi.org/10.1109/MWSCAS.1992.271387
Publication status	Published - 1992 Jan 1
Externally published	Yes
Event	35th Midwest Symposium on Circuits and Systems, MWSCAS 1992 - Washington, United States Duration: 1992 Aug 9 → 1992 Aug 12

Publication series

Name	Midwest Symposium on Circuits and Systems
Volume	1992-August
ISSN (Print)	1548-3746

Conference

Conference	35th Midwest Symposium on Circuits and Systems, MWSCAS 1992
Country/Territory	United States
City	Washington
Period	92/8/9 → 92/8/12

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/MWSCAS.1992.271387

Cite this

Ko, H., Baran, R., & Arozullah, M. (1992). Neural network based novelty filtering for signal detection enhancement. In 1992 Proceedings of the 35th Midwest Symposium on Circuits and Systems (pp. 252-255). [271387] (Midwest Symposium on Circuits and Systems; Vol. 1992-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MWSCAS.1992.271387

Neural network based novelty filtering for signal detection enhancement. / Ko, Hanseok; Baran, Robert; Arozullah, Mohammed.

1992 Proceedings of the 35th Midwest Symposium on Circuits and Systems. Institute of Electrical and Electronics Engineers Inc., 1992. p. 252-255 271387 (Midwest Symposium on Circuits and Systems; Vol. 1992-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ko, H, Baran, R & Arozullah, M 1992, Neural network based novelty filtering for signal detection enhancement. in 1992 Proceedings of the 35th Midwest Symposium on Circuits and Systems., 271387, Midwest Symposium on Circuits and Systems, vol. 1992-August, Institute of Electrical and Electronics Engineers Inc., pp. 252-255, 35th Midwest Symposium on Circuits and Systems, MWSCAS 1992, Washington, United States, 92/8/9. https://doi.org/10.1109/MWSCAS.1992.271387

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series = "Midwest Symposium on Circuits and Systems",

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AB - This paper concerns the analytical basis for designing adaptive novelty filter (ANF), based on a multilayer feedforward neural network, 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 pre-processor 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.

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BT - 1992 Proceedings of the 35th Midwest Symposium on Circuits and Systems

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Neural network based novelty filtering for signal detection enhancement

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

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