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Proceedings Paper

Maneuver detection algorithm based on probability density function estimation with use of RBF and HRBF neural network
Author(s): Krzystof Konopko; Dariusz Janczak
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Paper Abstract

The paper presents a new maneuver detection algorithm used in variable state dimension estimator. The proposed method is based on statistical test of two hypothesis which checks probability density function of innovation process of a tracking filter. The neural networks with radial and hyperradial basis functions are applied as probability density function and distribution function estimators. The results of numerical simulations are presented. The presented approach is also suitable for fault detection and diagnosis in dynamical systems.

Paper Details

Date Published: 22 July 2004
PDF: 5 pages
Proc. SPIE 5484, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments II, (22 July 2004); doi: 10.1117/12.569069
Show Author Affiliations
Krzystof Konopko, Bialystok Technical Univ. (Poland)
Dariusz Janczak, Bialystok Technical Univ. (Poland)


Published in SPIE Proceedings Vol. 5484:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments II
Ryszard S. Romaniuk, Editor(s)

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