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Multilayer optical learning networks

Wagner, Kelvin and Psaltis, Demetri (1987) Multilayer optical learning networks. Applied Optics, 26 (23). pp. 5061-5076. ISSN 0003-6935. http://resolver.caltech.edu/CaltechAUTHORS:20120626-090038005

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Abstract

A new approach to learning in a multilayer optical neural network based on holographically interconnected nonlinear devices is presented. The proposed network can learn the interconnections that form a distributed representation of a desired pattern transformation operation. The interconnections are formed in an adaptive and self-aligning fashioias volume holographic gratings in photorefractive crystals. Parallel arrays of globally space-integrated inner products diffracted by the interconnecting hologram illuminate arrays of nonlinear Fabry-Perot etalons for fast thresholding of the transformed patterns. A phase conjugated reference wave interferes with a backward propagating error signal to form holographic interference patterns which are time integrated in the volume of a photorefractive crystal to modify slowly and learn the appropriate self-aligning interconnections. This multilayer system performs an approximate implementation of the backpropagation learning procedure in a massively parallel high-speed nonlinear optical network.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1364/AO.26.005061DOIUNSPECIFIED
http://www.opticsinfobase.org/ao/abstract.cfm?uri=ao-26-23-5061PublisherUNSPECIFIED
Additional Information:© 1987 Optical Society of America. Received 28 May 1987. The authors would like to acknowledge the numerous contributions to this work made by David Brady as well as useful discussions with Jeff Yu and Hyatt Gibbs. The work reported here was partially supported by DARPA, the Army Research Office, and the Air Force Office of Scientific Research.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
Army Research Office (ARO)UNSPECIFIED
Air Force Office of Scientific Research (AFOSR)UNSPECIFIED
Record Number:CaltechAUTHORS:20120626-090038005
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20120626-090038005
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:32080
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:28 Jun 2012 20:18
Last Modified:26 Dec 2012 15:23

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