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Applied Optics

Applied Optics


  • Vol. 37, Iss. 18 — Jun. 20, 1998
  • pp: 4027–4033

Application of neural networks to the inverse light scattering problem for spheres

Zbigniew Ulanowski, Zhenni Wang, Paul H. Kaye, and Ian K. Ludlow  »View Author Affiliations

Applied Optics, Vol. 37, Issue 18, pp. 4027-4033 (1998)

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A new approach suitable for solving inverse problems in multiangle light scattering is presented. The method takes advantage of multidimensional function approximation capability of radial basis function neural networks. An algorithm for training the networks is described in detail. It is shown that the radius and refractive index of homogeneous spheres can be recovered accurately and quickly, with maximum relative errors of the order of 10-3 and mean errors as low as 10-5. The influence of the angular range of available scattering data on the loss of information and inversion accuracy is investigated, and it is shown that more than two thirds of input data can be removed before substantial degradation of accuracy occurs.

© 1998 Optical Society of America

OCIS Codes
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(290.0290) Scattering : Scattering
(290.3200) Scattering : Inverse scattering
(290.5850) Scattering : Scattering, particles

Original Manuscript: October 24, 1997
Revised Manuscript: February 10, 1998
Published: June 20, 1998

Zbigniew Ulanowski, Zhenni Wang, Paul H. Kaye, and Ian K. Ludlow, "Application of neural networks to the inverse light scattering problem for spheres," Appl. Opt. 37, 4027-4033 (1998)

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