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Gaussian rough surfaces can be characterized by two roughness parameters, the root-mean-square height and correlation length. For accurate estimation of these parameters from measured surface height-profile, data samples with sufficiently long record length are necessary. In this letter, an expression of correlation length in terms of a surface slope function is introduced in order to estimate correlation length and analytical expression of the data record length required for accurate estimation is derived. The result shows that the method using the slope function can reduce the data record length approximately 60% as compared to the commonly employed method using the correlation function. In order to check the result, a Monte Carlo simulation is also carried out and the validity of the result is confirmed.

- Publication
- IEICE TRANSACTIONS on Electronics Vol.E93-C No.1 pp.89-93

- Publication Date
- 2010/01/01

- Publicized

- Online ISSN
- 1745-1353

- DOI
- 10.1587/transele.E93.C.89

- Type of Manuscript
- BRIEF PAPER

- Category

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Masahiko NISHIMOTO, Kohichi OGATA, "On the Estimation of Rough Surface Parameters from Surface Profile Data --- Correlation Length Estimate Using a Surface Slope Function ---" in IEICE TRANSACTIONS on Electronics,
vol. E93-C, no. 1, pp. 89-93, January 2010, doi: 10.1587/transele.E93.C.89.

Abstract: Gaussian rough surfaces can be characterized by two roughness parameters, the root-mean-square height and correlation length. For accurate estimation of these parameters from measured surface height-profile, data samples with sufficiently long record length are necessary. In this letter, an expression of correlation length in terms of a surface slope function is introduced in order to estimate correlation length and analytical expression of the data record length required for accurate estimation is derived. The result shows that the method using the slope function can reduce the data record length approximately 60% as compared to the commonly employed method using the correlation function. In order to check the result, a Monte Carlo simulation is also carried out and the validity of the result is confirmed.

URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.E93.C.89/_p

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@ARTICLE{e93-c_1_89,

author={Masahiko NISHIMOTO, Kohichi OGATA, },

journal={IEICE TRANSACTIONS on Electronics},

title={On the Estimation of Rough Surface Parameters from Surface Profile Data --- Correlation Length Estimate Using a Surface Slope Function ---},

year={2010},

volume={E93-C},

number={1},

pages={89-93},

abstract={Gaussian rough surfaces can be characterized by two roughness parameters, the root-mean-square height and correlation length. For accurate estimation of these parameters from measured surface height-profile, data samples with sufficiently long record length are necessary. In this letter, an expression of correlation length in terms of a surface slope function is introduced in order to estimate correlation length and analytical expression of the data record length required for accurate estimation is derived. The result shows that the method using the slope function can reduce the data record length approximately 60% as compared to the commonly employed method using the correlation function. In order to check the result, a Monte Carlo simulation is also carried out and the validity of the result is confirmed.},

keywords={},

doi={10.1587/transele.E93.C.89},

ISSN={1745-1353},

month={January},}

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TY - JOUR

TI - On the Estimation of Rough Surface Parameters from Surface Profile Data --- Correlation Length Estimate Using a Surface Slope Function ---

T2 - IEICE TRANSACTIONS on Electronics

SP - 89

EP - 93

AU - Masahiko NISHIMOTO

AU - Kohichi OGATA

PY - 2010

DO - 10.1587/transele.E93.C.89

JO - IEICE TRANSACTIONS on Electronics

SN - 1745-1353

VL - E93-C

IS - 1

JA - IEICE TRANSACTIONS on Electronics

Y1 - January 2010

AB - Gaussian rough surfaces can be characterized by two roughness parameters, the root-mean-square height and correlation length. For accurate estimation of these parameters from measured surface height-profile, data samples with sufficiently long record length are necessary. In this letter, an expression of correlation length in terms of a surface slope function is introduced in order to estimate correlation length and analytical expression of the data record length required for accurate estimation is derived. The result shows that the method using the slope function can reduce the data record length approximately 60% as compared to the commonly employed method using the correlation function. In order to check the result, a Monte Carlo simulation is also carried out and the validity of the result is confirmed.

ER -