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Proceedings Paper

Architectures For Real-Time Sequential Detection
Author(s): John S. Baras; Anthony LaVigna
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Paper Abstract

We present the sequential detection for diffusion type signals both in the fixed probability of error formulation and in the Bayesian formulation. The optimal strategy in both cases is a threshold policy with explicitly computable thresholds. We provide numerical schemes for approximating the revelant likelihood ratio and provide an architecture for real time signal processing.

Paper Details

Date Published: 25 November 1987
PDF: 6 pages
Proc. SPIE 0827, Real-Time Signal Processing X, (25 November 1987); doi: 10.1117/12.942051
Show Author Affiliations
John S. Baras, University of Maryland (United States)
Anthony LaVigna, University of Maryland (United States)

Published in SPIE Proceedings Vol. 0827:
Real-Time Signal Processing X
J. P. Letellier, Editor(s)

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