Published August 25, 1992
| Published
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Fast neural algorithms for detecting moving targets in highly noisy environments
- Creators
- Barhen, Jacob
- Toomarian, Nikzad
- Zak, Michail
- Other:
- Drummond, Oliver
Chicago
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Abstract
The detection of targets moving in an environment dominated by "noise" is addressed from the perspective of nonlinear dynamics. Sensor data are used to drive a Korteweg-deVries (soliton) equation, inducing a resonance-type phenomenon which indicates the presence of hidden target signals. The algorithm is implemented in terms of a novel neural architecture, which we have named "spectral network", which can easily be implemented in optoelectronic hardware.
Additional Information
© 1992 Society of Photo-Optical Instrumentation Engineers (SPIE). This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology. Support for the work came from the Naval Weapons Center, China Lake, California, through an agreement with the National Aeronautics and Space Administration. We thank A. Agranat, C. Neugebauer and A. Yariv (Caltech), as well as R. Tawel and A. Thakoor (JPL) for enlightening discussions concerning possible hardware implementation of our algorithms.Attached Files
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Additional details
- Eprint ID
- 81410
- Resolver ID
- CaltechAUTHORS:20170913-104611644
- Naval Weapons Center
- NASA
- Created
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2017-09-14Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field
- Series Name
- Proceedings of SPIE
- Series Volume or Issue Number
- 1698