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Proceedings Paper

Optimization of a lens design using a neural network
Author(s): John Macdonald; Amanda J. Breese; Nigel L. Hanbury
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Paper Abstract

The graded-response Hopfield neural network model has been used to solve the traveling salesman optimization problem. However, the mapping of an optical design optimization problem onto a neural net is more difficult. This paper describes how it can be done for the case of minimizing the chromatic aberration in a complicated twenty-element zoom-lens system by the selection of glass types. The problem is combinatorial in nature. It is suited to neural networks, and its solution is non-trivial by other means. Thus the use of neural networks to solve optical optimization problems is demonstrated.

Paper Details

Date Published: 2 September 1993
PDF: 12 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152573
Show Author Affiliations
John Macdonald, Univ. of Reading (United Kingdom)
Amanda J. Breese, Univ. of Reading (Canada)
Nigel L. Hanbury, Univ. of Reading (United Kingdom)


Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

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