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As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk.
Tests for departure from normality. Empirical results for the distributions of b 2 and√ b
RALPH D’AGOSTINO and Egon S Pearson. 1973 · 1973
Earlier work this paper cites.
The exponentially weighted moving average
J Stuart Hunter et al · 1986
Earlier work this paper cites.
An expert system for diagnosing environmentally induced spacecraft anomalies
M. Rolincikm, Lauriente M., Koons H., and D. Gorney. 1992 · 1991
Earlier work this paper cites.
Satellite diagnostic system: An expert system for intelsat satellite operations. In In Proceedings of the IVth European Aerospace Conference (EAC) . 321–327
Chang C., Nallo W., Rastogi R., Beugless D., Mickey F., and Shoop A. 1992 · 1992
Earlier work this paper cites.
Intelligent fault isolation and diagnosis for communication satellite systems
Donald P. Tallo, John Durkin, and Edward J. Petrik. 1992 · 1992
Earlier work this paper cites.
Event diagnosis and recovery in real-time on-board autonomous mission control
F. Ciceri and L. Marradi. 1994 · 1994
Earlier work this paper cites.
Long Short-Term Memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Nonlinear Component Analysis As a Kernel Eigenvalue Problem
Bernhard Schölkopf, Alexander Smola, and Klaus-Robert Müller. 1998 · 1998
Earlier work this paper cites.
Autonomy and software technology on NASA’s Deep Space One
D. Bernard, R. Doyle, E. Riedel, N. Rouquette, J. Wyatt, M. Lowry, and P. Nayak. 1999 · 1999
Earlier work this paper cites.
LOF: Identifying Density-Based Local Outliers. In PROCEEDINGS OF THE 2000 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA . ACM, 93–104
Markus Breunig, Hans-Peter Kriegel, Raymond T. Ng, and Jörg Sander. 2000 · 2000
Earlier work this paper cites.
Lessons from implementation of beacon spacecraft operations on Deep Space One. In 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484) . IEEE
R. Sherwood, A. Schlutsmeyer, M. Sue, and E.J. Wyatt. [n. d.] · 2000
Earlier work this paper cites.
Overfitting in neural nets: Backpropagation, conjugate gradient, and early stopping. In Advances in neural information processing systems . 402–408
Rich Caruana, Steve Lawrence, and C Lee Giles. 2001 · 2001
Earlier work this paper cites.
Fully Automatic and Operator-less Anomaly Detecting Ground Support System For Mars Probe "NOZOMI". In In Proceedings of the 6th International Symposium on Artificial Intelligence and Robotics and Automation in Space (i-SAIRAS)
Naomi Nishigori and Fujitsu Limited. 2001 · 2001
Earlier work this paper cites.
Mining Distance-based Outliers in Near Linear Time with Randomization and a Simple Pruning Rule. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’03) . ACM, New York, NY, USA, 29–38
Stephen D. Bay and Mark Schwabacher. 2003 · 2003
Earlier work this paper cites.
Inductive system health monitoring. In In Proceedings of The 2004 International Conference on Artificial Intelligence (IC-AI04), Las Vegas . CSREA Press
David L. Iverson. 2004 · 2004
Earlier work this paper cites.
An Approach to Spacecraft Anomaly Detection Problem Using Kernel Feature Space. In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining (KDD ’05) . ACM, New York, NY, USA, 401–410
Ryohei Fujimaki, Takehisa Yairi, and Kazuo Machida. 2005 · 2005
Cited alongside, same era.
Telemetry-mining: A Machine Learning Approach to Anomaly Detection and Fault Diagnosis for Space Systems. In 2nd IEEE International Conference on Space Mission Challenges for Information Technology . IEEE
Yoshinobu Kawahara Takehisa Yairi. [n. d.] · 2006
Cited alongside, same era.
Data Mining Applications for Space Mission Operations System Health Monitoring. In SpaceOps 2008 Conference . American Institute of Aeronautics and Astronautics
David Iverson. 2008 · 2008
Cited alongside, same era.
Anomaly Detection: A Survey
Varun Chandola, Arindam Banerjee, and Vipin Kumar. 2009 · 2009
Cited alongside, same era.
Improving Spacecraft Health Monitoring with Automatic Anomaly Detection Techniques. In 14th International Conference on Space Operations (SpaceOps 2016) . pp–1
Sylvain Fuertes, Gilles Picart, Jean-Yves Tourneret, Lotfi Chaari, André Ferrari, and Cédric Richard. 2016 · 2016
Later among the works it cites.
A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data
Markus Goldstein and Seiichi Uchida. 2016 · 2016
Later among the works it cites.
Deep learning . Vol. 1
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio. 2016 · 2016
Later among the works it cites.
A novel method for spacecraft electrical fault detection based on FCM clustering and WPSVM classification with PCA feature extraction
Ke Li, Yalei Wu, Shimin Song, Yi sun, Jun Wang, and Yang Li. 2016 · 2016
Later among the works it cites.
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, and Gautam Shroff. 2016 · 2016
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Anomaly detection and fault Diagnosis technology of spacecraft based on telemetry-mining. In 2010 3rd International Symposium on Systems and Control in Aeronautics and Astronautics . IEEE
Quan Li, XingShe Zhou, Peng Lin, and Shaomin Li. 2010 · 2010
Cited alongside, same era.
An Unsupervised Anomaly Detection Approach for Spacecraft Based on Normal Behavior Clustering. In 2012 Fifth International Conference on Intelligent Computation Technology and Automation . IEEE
Yu Gao, Tianshe Yang, Minqiang Xu, and Nan Xing. 2012 · 2012
Cited alongside, same era.
Supervised Sequence Labelling with Recurrent Neural Networks
Alex Graves. 2012 · 2012
Cited alongside, same era.
Speech Recognition with Deep Recurrent Neural Networks
Alex Graves, Abdel rahman Mohamed, and Geoffrey Hinton. 2013 · 2013
Cited alongside, same era.
Enhanced Telemetry Monitoring with Novelty Detection
Jose Martínez-Heras and Alessandro Donati. 2014 · 2014
Cited alongside, same era.
Haşim Sak, Andrew Senior, and Françoise Beaufays. 2014 · 2014
Cited alongside, same era.
Deep learning in neural networks: An overview
Jürgen Schmidhuber. 2015 · 2014
Cited alongside, same era.
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
Cited alongside, same era.
Later among the works it cites.
Anomaly detection in aircraft data using Recurrent Neural Networks (RNN)
Anvardh Nanduri and Lance Sherry. 2016 · 2016
Later among the works it cites.
Nonlinear Systems Identification Using Deep Dynamic Neural Networks
Olalekan Ogunmolu, Xuejun Gu, Steve Jiang, and Nicholas Gans. 2016 · 2016
Later among the works it cites.
Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks. In 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA) . IEEE
Adrian Taylor, Sylvain Leblanc, and Nathalie Japkowicz. 2016 · 2016
Later among the works it cites.
Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling
Peng Zhou, Zhenyu Qi, Suncong Zheng, Jiaming Xu, Hongyun Bao, and Bo Xu. 2016 · 2016
Later among the works it cites.
Unsupervised real-time anomaly detection for streaming data
Subutai Ahmad, Alexander Lavin, Scott Purdy, and Zuha Agha. 2017 · 2017
Later among the works it cites.
Collective Anomaly Detection based on Long Short Term Memory Recurrent Neural Network
Loic Bontemps, Van Loi Cao, James McDermott, and Nhien-An Le-Khac. 2017 · 2017
Later among the works it cites.
Report of the Europa Lander Science Definition Team
KP Hand, AE Murray, JB Garvin, WB Brinckerhoff, BC Christner, KS Edgett, BL Ehlmann, C German, AG Hayes, TM Hoehler, et al · 2017
Later among the works it cites.
Dominique T. Shipmon, Jason M. Gurevitch, Paolo M. Piselli, and Stephen T. Edwards. 2017 · 2017
Later among the works it cites.
Recent Trends in Deep Learning Based Natural Language Processing
Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria. 2017 · 2017
Later among the works it cites.
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