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10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems
Real-Time Data Fusion Technique for Validation of an Autonomous System
Sedona, Arizona
February 02-February 04
ISBN: 0-7695-2347-1
ASCII Text
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Bojan Cukic, Martin Mladenovski, Dejan Desovski, Sampath Yerramalla, "Real-Time Data Fusion Technique for Validation of an Autonomous System," Object-Oriented Real-Time Dependable Systems, IEEE International Workshop on, pp. 121-128, 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems, 2005.
 
 
BibTex
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@article{ 10.1109/WORDS.2005.48,
author = {Bojan Cukic and Martin Mladenovski and Dejan Desovski and Sampath Yerramalla},
title = {Real-Time Data Fusion Technique for Validation of an Autonomous System},
journal ={Object-Oriented Real-Time Dependable Systems, IEEE International Workshop on},
volume = {0},
year = {2005},
issn = {1530-1443},
pages = {121-128},
doi = {http://doi.ieeecomputersociety.org/10.1109/WORDS.2005.48},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Object-Oriented Real-Time Dependable Systems, IEEE International Workshop on
TI - Real-Time Data Fusion Technique for Validation of an Autonomous System
SN - 1530-1443
SP121
EP128
A1 - Bojan Cukic,
A1 - Martin Mladenovski,
A1 - Dejan Desovski,
A1 - Sampath Yerramalla,
PY - 2005
KW - null
VL - 0
JA - Object-Oriented Real-Time Dependable Systems, IEEE International Workshop on
ER -
 
Bojan Cukic, Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV
Martin Mladenovski, Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV
Dejan Desovski, Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV
Sampath Yerramalla, Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV

We describe a data fusion technique suitable for use in validation of a real-time autonomous system. The technique is based on the Dempster-Shafer theory and Murhpy?s rule for beliefs combination.

The methodology is applied for fusing the learning stability estimates, provided by an online neural network monitoring methodology, into a single probabilistic learning stability measure. The case study shows that our data fusion technique is capable of handing real-time requirements and provides unique, meaningful results for interpreting the stability information provided by the online monitoring system.

Citation:
Bojan Cukic, Martin Mladenovski, Dejan Desovski, Sampath Yerramalla, "Real-Time Data Fusion Technique for Validation of an Autonomous System," words, pp.121-128, 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems, 2005
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