First results of an on-line adaptive optics system with atmospheric wavefront sensing by an artificial neural network

1992 ◽  
Vol 390 ◽  
pp. L41 ◽  
Author(s):  
M. Lloyd-Hart ◽  
P. Wizinowich ◽  
B. McLeod ◽  
D. Wittman ◽  
D. Colucci ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Adaptive Optics ◽  
Wavefront Sensing ◽  
First Results ◽  
On Line ◽  
Artificial Neural ◽  
Adaptive Optics System

Artificial Neural Network and the Taguchi Method Application for Robust Wheatstone Bridge Design

1994 ◽  
Author(s):  
Jung-eui Hong ◽  
Cihan H. Dagli ◽  
Kenneth M. Ragsdell
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wheatstone Bridge ◽  
Parameter Design ◽  
System Response ◽  
Measurement Circuit ◽  
Wide Range ◽  
Reduce Measurement Error ◽  
On Line ◽  
Artificial Neural

Abstract The primary function of the Wheatstone bridge is to measure an unknown resistance. The elements of this well-known measurement circuit will take on different values depending upon the range and accuracy required for a particular application. The Taguchi approach to parameter design is used to select values for the measurement circuit elements so as to reduce measurement error. Next we introduce the use of an artificial neural network to extrapolate limited experimental results to predict system response over a wide range of applications. This approach can be employed for on-line quality control of the manufacture of such device.

Hartmann wavefront sensing with an artificial neural network processor

1994 ◽  
Author(s):  
Eli Ettedgui-Atad ◽  
G. Catalan ◽  
John W. Harris ◽  
Colin M. Humphries ◽  
A. M. Smillie ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Processor ◽  
Wavefront Sensing ◽  
Artificial Neural
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