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Early Detection of Combustion Instability by Neural-Symbolic Analysis on Hi-Speed Video.

, , and . CoCo@NIPS, volume 1583 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)

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Symbolization of dynamic data-driven systems for signal representation., , and . Signal Image Video Process., 10 (8): 1535-1542 (2016)Spatiotemporal information fusion for fault detection in shipboard auxiliary systems., , , , and . ACC, page 3846-3851. IEEE, (2013)A unified framework for supervised learning of semantic models., , , , and . ACC, page 2183-2188. IEEE, (2012)Context-aware Dynamic Data-driven Pattern Classification., , , , , and . ICCS, volume 29 of Procedia Computer Science, page 1324-1333. Elsevier, (2014)Sensor Fusion for Fault Detection and Classification in Distributed Physical Processes., , , , and . Front. Robotics and AI, (2014)Multimodal spatiotemporal information fusion using neural-symbolic modeling for early detection of combustion instabilities., , , , and . ACC, page 4918-4923. IEEE, (2016)Dynamic data-driven symbolic causal modeling for battery performance & health monitoring., , , and . FUSION, page 1395-1402. IEEE, (2015)Early Detection of Combustion Instability by Neural-Symbolic Analysis on Hi-Speed Video., , and . CoCo@NIPS, volume 1583 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Real-time activity recognition from seismic signature via multi-scale symbolic time series analysis (MSTSA)., , and . ACC, page 5818-5823. IEEE, (2015)Anomaly detection in flight recorder data: A dynamic data-driven approach., , , , and . ACC, page 2668-2673. IEEE, (2013)