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Proceedings Paper

Optical data association neural net
Author(s): David P. Casasent; Mark L. Yee
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Paper Abstract

This paper presents new results of our data association (DA) neural net (NN) on measurement-to-estimate data (rather than measurement-to-measurement data). It also uses our detection unit. Our new jitter model is discussed and initial results are presented. This also includes tests of our fixed coefficient estimator and initial optical laboratory results.

We find that: the use of an estimator improves DA MN results (since no clutter is present in the estimate frame), reduction of jitter by using the detection system in tracking helps, our system handles measurement noise and jitter and clutter with no loss of track, and our fixed coefficient estimator suffices.

Paper Details

Date Published: 2 February 1993
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Proc. SPIE 1773, Photonics for Computers, Neural Networks, and Memories, (2 February 1993); doi: 10.1117/12.983195
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Mark L. Yee, Sandia National Labs. (United States)


Published in SPIE Proceedings Vol. 1773:
Photonics for Computers, Neural Networks, and Memories
Stephen T. Kowel; John A. Neff; William J. Miceli, Editor(s)

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