Biologically motivated quantum neural networks

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Authors
Steck, James E.
Behrman, Elizabeth C.
Advisors
Issue Date
2017
Type
Conference paper
Keywords
Deep , Recognition , Computation
Research Projects
Organizational Units
Journal Issue
Citation
Steck, James E.; Behrman, Elizabeth C. 2017. Biologically motivated quantum neural networks. 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp 1030-1034
Abstract

This paper presents one step toward creating the building blocks for machine intelligence that is inspired by its biological equivalent. The authors' quantum learning methods (deep quantum learning) are applied to quantum devices whose quantum bit (q-bit) activity is deliberately chosen to mimic the spiking behavior of biological neurons. Because of the "quantum" scale of these computers, these studies may lead to quantum hardware (rather than simulation) with enough processors and enough connectivity that can more closely mimic biological intelligence.

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Publisher
IEEE
Journal
Book Title
Series
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC);
PubMed ID
DOI
ISSN
1062-922X
EISSN