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Proceedings Paper

Application of the Lockheed programmable analog neural network breadboard to the real-time adaptive mirror control problem
Author(s): William A. Fisher; Robert J. Fujimoto; James R. Roehrig; Robert C. Smithson
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Paper Abstract

A neural network breadboard consisting of 256 neurons and with 2048 5 bit programmable synaptic weights has been constructed and is in use to demonstrate as a real time adaptive mirror control. The heart of the system is an array of custom 8 wide programmable resistor chips on a reconfigurable neuron board. The current system can processes a frame of 138 slope measurements producing 69 actuator position control signals at a rate ofup to 5000 frames per second. This system was designed to replace a conventional approach using a STAR array processor which is limited to a frame rate of less than 600 frames/sec. The 5000 frame/sec data rate is limited by the digital bandwidth of the wavefront sensor but still represents an equivalent processing speed of 140 megaflops. The analog bandwidth of the resistor/neuron board is better than 90 kHz which would allow frame rates as high as 900 kHz. The system architecture is expandable with complexity proportional to the number of actuators. The control algorithm is a variation of Hudgin''s algorithm modified to allow flexibility in the hardware setup. A specialized version of the LMS algorithm is used to train a sparsened pseudo-inverse response weight matrix and a geometrically determined feedback weight matrix. The training can be run while the analog network controls the mirror in real time. This allows the wavefront control algorithm to adjust to thermally induced

Paper Details

Date Published: 1 August 1990
PDF: 9 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21177
Show Author Affiliations
William A. Fisher, Lockheed Palo Alto Research La (United States)
Robert J. Fujimoto, Lockheed Palo Alto Research La (United States)
James R. Roehrig, Lockheed Palo Alto Research La (United States)
Robert C. Smithson, Lockheed Palo Alto Research La (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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