NEURAL NETWORKS FOR BINARIZING COMPUTER-GENERATED HOLOGRAMS

被引：8
|
作者：
JUST, D
LING, DT
机构：
[1] IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598
来源：
OPTICS COMMUNICATIONS | 1991年 / 81卷 / 1-2期
关键词：
D O I：
10.1016/0030-4018(91)90282-I
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
A Hopfield type neural network was applied to compute synthetic, binary holograms. This iterative neuron algorithm minimizes reconstruction errors in amplitude and phase. About twenty iteration steps are sufficient for convergence, each of them has the computational complexity of a FFT. In addition, the neural net is flexible to include a variety of optimization strategies.
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页码：1 / 5
页数：5
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