@article{eef4402943fa441585bebd2ffa89cc2b,
title = "Surface Roughness Determination Using Spectral Correlations of Scattered Intensities and an Artificial Neural Network Technique",
abstract = "An artificial neural network (ANN) technique is applied to the determination of the rms height and the correlation distance of one-dimensional rough surfaces. The surface is illuminated by a beam wave, and the intensity correlations of the scattered wave at two wavelengths in the specular and backward directions are used to determine the roughness parameters. Scattered intensity correlations calculated by Monte Carlo simulations are used to train the ANN, and two methods, the explicit inversion method and the iterative constrained inversion method, are used to perform the inversion. The inversion values are compared with the target values, and the iterative constrained method is shown to give smaller errors, but requires longer computer CPU time.",
author = "Kuniaki Yoshitomi and Akira Ishimaru and Hwang, {Jeng Neng} and Chen, {Jei Shuan}",
note = "Funding Information: Next, the inverse problem of finding the surface parameters, U and 1, from the measurement is considered. Here we use an artificial Manuscript received December 10, 1991; revised December 7, 1992. This work was supported by the National Science Foundation and the U.S. Army Research Office. K. Yoshitomi is with the Department of Computer Science and Communication Engineering, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812, Japan. A. Ishimaru and J.-N. Hwang are with the Department of Electrical Engineering, University of Washington, Seattle, WA 98185. J. S. Chen is with the Lockheed Palo Alto Research Laboratory, Sunnyvale, CA 94088. IEEE Log Number 9208 134.",
year = "1993",
month = apr,
doi = "10.1109/8.220983",
language = "English",
volume = "41",
pages = "498--502",
journal = "IEEE Transactions on Antennas and Propagation",
issn = "0018-926X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",
}