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OPTICAL COMPUTING IN BOLTZMANN MACHINES.

This dissertation covers theoretical and experimental work on applying optical processing techniques ot the operation of a Boltzmann machine. A Boltzmann machine is a processor that solves a problem by iteratively optimizing an estimate of the solution. The optimization is done by finding a minimum of an energy surface over the solution space. The energy function is designed to consider not only data but also a priori information about the problem to assist the optimization. The dissertation first establishes a generic line-of-approach for designing an algorithmic optical computer that might successfully operate using currently realizable analog optical systems for highly-parallel operations. Simulated annealing, the algorithm of the Boltzmann machine, is then shown to be adaptable to this line-of-approach and is chosen as the algorithm to demonstrate these concepts throughout the dissertation. The algorithm is analyzed and optical systems are outlined that will perform the appropriate tasks within the algorithm. From this analysis and design, realizations of the optically-assisted Boltzmann machine are described and it is shown that the optical systems can be used in these algorithmic computations to produce solutions as precise as the single-pass operations of the analog optical systems. Further considerations are discussed for increasing the usefulness of the Boltzmann machine with respect to operating on larger data sets while maintaining the full degrees of parallelism and to increasing the speed by reducing the number of electronical-optical transducers and by utilizing more of the available parallelism. It is demonstgrated how, with a little digital support, the analog optical systems can be used to produce solutions with digital precision but without compromising the speed of the optical computations. Finally there is a short discussion as to how the Boltzmann machine may be modelled as a neuromorphic system for added insight into the computational functioning of the machine.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/184169
Date January 1987
CreatorsTICKNOR, ANTHONY JAMES.
ContributorsBarrett, Harry
PublisherThe University of Arizona.
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
Typetext, Dissertation-Reproduction (electronic)
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

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