Architecture Developed for Monitoring and Anomaly Detection of Space Systems
Researchers at the University of Central Florida have found that by incorporating analysis and monitoring algorithms, such as Inductive Monitoring System, neural networks, and recent advances in deep learning within the architecture’s signal processing system, engineers have a flexible and powerful end-to-end data analysis and monitoring system for instrumented remote aerospace hardware. Read more at http://articles.sae.org/12861 .
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