Neural network approach to multipath delay estimation

Stephen T. Welstead; Michael J. Ward; Christopher W. Keefer

doi:10.1117/12.49800

1 December 1991 Neural network approach to multipath delay estimation

Stephen T. Welstead, Michael J. Ward, Christopher W. Keefer

Proceedings Volume 1565, Adaptive Signal Processing; (1991) https://doi.org/10.1117/12.49800
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

Stephen T. Welstead, Michael J. Ward, and Christopher W. Keefer "Neural network approach to multipath delay estimation", Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); https://doi.org/10.1117/12.49800

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available