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Proceedings Paper

Fast neural algorithms for detecting moving targets in highly noisy environments
Author(s): Jacob Barhen; Nikzad Toomarian; Michail Zak
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Paper 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.

Paper Details

Date Published: 25 August 1992
PDF: 10 pages
Proc. SPIE 1698, Signal and Data Processing of Small Targets 1992, (25 August 1992); doi: 10.1117/12.139392
Show Author Affiliations
Jacob Barhen, California Institute of Technology (United States)
Nikzad Toomarian, California Institute of Technology (United States)
Michail Zak, California Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1698:
Signal and Data Processing of Small Targets 1992
Oliver E. Drummond, Editor(s)

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