Numerical model of adaptive optical system controlled by a feedforward neural network

Gleb V. Vdovin

doi:10.1117/12.217752

25 August 1995 Numerical model of adaptive optical system controlled by a feedforward neural network

Gleb V. Vdovin

Proceedings Volume 2534, Adaptive Optical Systems and Applications; (1995) https://doi.org/10.1117/12.217752
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

An adaptive optical system (AOS) with a feedback loop closed via feedforward neural network (NN) is considered. The vector of the wavefront corrector control signals is computed by the network from two vectors of the intensity moments measured in two near-field planes by two matrix photo-detectors. The NN is trained with back-propagation algorithm to predict the vector of AM signals from the measured intensity vectors. During training phase the network forms a control algorithm for a given configuration of the optical system, taking into account misalignments and nonlinearities of the hardware used. A numerical model of a multichannel AOS controlled by a multilayer NN has been built, trained, and run for different low-order input aberrations. The neural control permits a direct conversion of the intensity distribution measured in the near field into control signals of the wavefront corrector. High efficiency of control has been demonstrated for a model of a 16-channel adaptive optical system for arbitrary input aberrations having limited spatial spectrum.

Citation Download Citation

Gleb V. Vdovin "Numerical model of adaptive optical system controlled by a feedforward neural network", Proc. SPIE 2534, Adaptive Optical Systems and Applications, (25 August 1995); https://doi.org/10.1117/12.217752

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