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Proceedings Paper

Neural network approach to multipath delay estimation
Author(s): Stephen T. Welstead; Michael J. Ward; Christopher W. Keefer
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Paper Abstract

Neural networks can be applied to the problem of extracting multipath delay information from the correlation of two signals. The ability of a feedforward neural network to learn the correct delay vector response is demonstrated using both broadband and narrowband correlation data. A trained neural network can be combined with a traditional adaptive algorithm for systems applications such as adaptive interference cancellation. In many cases, the network improves overall system performance by providing a nearly optimal starting point. The use of such an approach in an existing optical processing architecture is discussed.

Paper Details

Date Published: 1 December 1991
PDF: 10 pages
Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); doi: 10.1117/12.49800
Show Author Affiliations
Stephen T. Welstead, COLSA, Inc. (United States)
Michael J. Ward, Rome Lab. (United States)
Christopher W. Keefer, Rome Lab. (United States)

Published in SPIE Proceedings Vol. 1565:
Adaptive Signal Processing
Simon Haykin, Editor(s)

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