An Investigation of the Application of Artificial Neural Networks to Adaptive Optics Imaging Systems

Author

Andrew H. Suzuki

Date of Award

12-1991

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Byron M. Welsh, PhD

Abstract

Recurrent and feedforward artificial neural networks are developed as wavefront reconstructors. The recurrent neural network studied is the Hopfield neural network and the feedforward neural network studied is the single layer perceptron artificial neural network. The recurrent artificial neural network input features are the wavefront sensor slope outputs and neighboring actuator feedback commands. The feedforward artificial neural network input features are just the wavefront sensor slope outputs. Both artificial neural networks use their inputs to calculate deformable mirror actuator commands. The effects of training are examined.

AFIT Designator

AFIT-GEO-ENG-91D-04

DTIC Accession Number

ADA243780

Comments

The author's Vita page is omitted.

Recommended Citation

Suzuki, Andrew H., "An Investigation of the Application of Artificial Neural Networks to Adaptive Optics Imaging Systems" (1991). Theses and Dissertations. 7593.
https://scholar.afit.edu/etd/7593