Optimization of a lens design using a neural network

John Macdonald; Amanda J. Breese; Nigel L. Hanbury

doi:10.1117/12.152573

2 September 1993 Optimization of a lens design using a neural network

John Macdonald, Amanda J. Breese, Nigel L. Hanbury

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152573
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

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.

Citation Download Citation

John Macdonald, Amanda J. Breese, and Nigel L. Hanbury "Optimization of a lens design using a neural network", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152573

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