49 lines
2.6 KiB
Markdown
49 lines
2.6 KiB
Markdown
---
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title: "Data fusion"
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chunk: 2/2
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source: "https://en.wikipedia.org/wiki/Data_fusion"
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category: "reference"
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tags: "science, encyclopedia"
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date_saved: "2026-05-05T09:53:51.162435+00:00"
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instance: "kb-cron"
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---
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== For enhanced contextual awareness ==
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With a multitude of built-in sensors including motion sensor, environmental sensor, position sensor, a modern mobile device typically gives mobile applications access to a number of sensory data which could be leveraged to enhance the contextual awareness. Using signal processing and data fusion techniques such as feature generation, feasibility study and principal component analysis (PCA) such sensory data will greatly improve the positive rate of classifying the motion and contextual relevant status of the device. Many context-enhanced information techniques are provided by Snidaro, et al.
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== Statistical methods ==
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=== Bayesian auto-regressive Gaussian processes ===
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Gaussian processes are a popular machine learning model. If an auto-regressive relationship between the data is assumed, and each data source is assumed to be a Gaussian process, this constitutes a non-linear Bayesian regression problem.
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=== Semiparametric estimation ===
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Many data fusion methods assume common conditional distributions across several data sources. Recently, methods have been developed to enable efficient estimation within the resulting semiparametric model.
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== See also ==
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Data assimilation
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Data munging
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Image fusion
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Information integration
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Integrative level
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Meta-analysis
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Sensor fusion
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== References ==
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=== Sources ===
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General references
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Hall, Dave L.; Llinas, James (1997). "Introduction to Multisensor Data Fusion". Proceedings of the IEEE. 85 (1): 6–23. doi:10.1109/5.554205.
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Blasch, Erik; Kadar, Ivan; Salerno, John; Kokar, Mieczyslaw M.; Das, Subrata; Powell, Gerald M.; Corkill, Daniel D.; Ruspini, Enrique H. (2006). "Issues and Challenges in Situation Assessment (Level 2 Fusion)" (PDF). Journal of Advances in Information Fusion. 1 (2). Archived from the original (PDF) on 2015-05-27.
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== Bibliography ==
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Hall, David L.; McMullen, Sonya A. H. (2004). Mathematical Techniques in Multisensor Data Fusion, Second Edition. Norwood, MA: Artech House, Inc. ISBN 978-1-5805-3335-5.
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Mitchell, H. B. (2007). Multi-sensor Data Fusion – An Introduction. Berlin: Springer-Verlag. ISBN 978-3-540-71463-7.
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Das, S. (2008). High-Level Data Fusion. Norwood, MA: Artech House Publishers. ISBN 978-1-59693-281-4.
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== External links ==
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Discriminant Correlation Analysis (DCA)
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Sensordata Fusion, An Introduction
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International Society of Information Fusion
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Sensor Fusion for Nanopositioning |