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Autoregressive process for characterizing statistically rough surfaces

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Abstract

It is shown that rough surfaces of thin silver films deposited on LiF underlayers may be accurately described by a low-order autoregressive process. The autoregressive (AR) parameters are determined, and the advantages of describing statistically rough surfaces of thin deposits by linear models instead of with the traditional autocovariance function (ACF) or the profile power-spectral-density function (PPSDF) are discussed.

© 1993 Optical Society of America

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