Abstract
In this chapter the fundamentals of statistical parameter estimation are reviewed for applications typical in experimental fluid mechanics. The chapter begins with a review of the probability density function and its moments and continues with common estimators for the mean and variance of stationary random processes. A brief introduction to signal noise is given as a prelude to a rigorous discussion of the Cramér–Rao Lower Bound (CRLB). The CRLB represents the lower bound of variance of unbiased estimators of a parameter. This concept is deepened using illustrations from the laser Doppler, phase Doppler and PIV measurement techniques. The chapter closes with a short discussion about the propagation of errors in a measurement chain.
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Abbreviations
- ACF:
-
autocorrelation function
- CRLB:
-
Cramér–Rao lower bound
- ML:
-
maximum-likelihood
- MLE:
-
maximum-likelihood estimator
- PDF:
-
probability density function
- PIV:
-
particle image velocimetry
- PSD:
-
particle size distribution
- PSD:
-
power spectral density
- SNR:
-
signal-to-noise ratio
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© 2007 Springer-Verlag
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Nobach, H., Tropea, C. (2007). Fundamentals of Data Processing. In: Tropea, C., Yarin, A.L., Foss, J.F. (eds) Springer Handbook of Experimental Fluid Mechanics. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30299-5_23
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DOI: https://doi.org/10.1007/978-3-540-30299-5_23
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