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Fundamentals of Data Processing

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Springer Handbook of Experimental Fluid Mechanics

Part of the book series: Springer Handbooks ((SHB))

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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Correspondence to Holger Nobach or Cameron Tropea Dr. .

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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25141-5

  • Online ISBN: 978-3-540-30299-5

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