Bayesian signal analysis (BSA)
Published: March 30, 2010, 12:00 am
Updated: July 2, 2012, 5:08 pm
This article has been reviewed by the following Topic Editor:
C Michael Hogan
Bayesian signal analysis (BSA) is a method designed to be optimal for analyzing a relatively short time series, which method can work with a Signal-to-Noise Ratio (SNR) as low as 0.6. No apriori hypotheses are made about the actual series belonging to any hypothetical ensemble or infinite series; only the given data are used to find the probability of some a priori signal being contained in the data. A measure of the analysis accuracy of the estimate can also be obtained.
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This article is written at a definitional level only. Authors wishing to expand this entry are inivited to expand the present treatment, which additions will be peer reviewed prior to publication of any expansion. |
Further Reading
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Friedman, N.; Linial, M.; Nachman, I.; Pe'er, D. (2000). "Using Bayesian Networks to Analyze Expression Data". Journal of Computational Biology 7 (3–4): 601–620.
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Citation
Steve Baum (Lead Author);C Michael Hogan (Topic Editor) "Bayesian signal analysis (BSA)". In: Encyclopedia of Earth. Eds. Cutler J. Cleveland (Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment). [First published in the Encyclopedia of Earth March 30, 2010; Last revised Date July 2, 2012; Retrieved May 20, 2013 <http://www.eoearth.org/article/Bayesian_signal_analysis_(BSA)>
The Author
Assistant Research Scientist, Physical Section
Department of Oceanography
Texas A&M University ... (Full Bio)
Bayesian signal analysis (BSA) is a method designed to be optimal for analyzing a relatively short time series, which method can work with a Signal-to-Noise Ratio (SNR) as low as 0.6. No apriori hypotheses are made about the actual series belonging to any hypothetical ensemble or infinite series; only the given data are used to find the probability of some a priori signal being contained in the data. A measure of the analysis accuracy of the estimate can also be obtained.
|
This article is written at a definitional level only. Authors wishing to expand this entry are inivited to expand the present treatment, which additions will be peer reviewed prior to publication of any expansion. |
Further Reading
-
Friedman, N.; Linial, M.; Nachman, I.; Pe'er, D. (2000). "Using Bayesian Networks to Analyze Expression Data". Journal of Computational Biology 7 (3–4): 601–620.
-
Physical Oceanography Index
Are you absolutely sure you want to delete this article? This process cannot be undone and is permanent.
Yes, Delete This Article
Are you absolutely sure you want to remove this article? This process cannot be undone and is permanent.
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