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Proceedings Paper

Memristor-based pattern recognition for image processing: an adaptive coded aperture imaging and sensing opportunity
Author(s): Chris Yakopcic; Tarek M. Taha; Guru Subramanyam; Eunsung Shin; P. Terrence Murray; Stanley Rogers
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Paper Abstract

Adaptive coded aperture (diffraction) sensing, an emerging technology enabling real-time, wide-area IR/visible sensing and imaging, could benefit from new high performance biologically inspired image processing architectures. The memristor, a novel two terminal passive device can enable significantly powerful biologically inspired processing architectures. This device was first theorized by Dr. Leon Chua in 1971. In 2008, HP Labs successfully fabricated the first memristor devices. Due to its unique properties, the memristor can be used to implement neuromorphic functions as its dynamics closely model those of a synapse, and can thus be utilized in biologically inspired processing architectures. This paper uses existing device models to determine how device parameters can be tuned for the memristor to be used in neuromorphic circuit design. Specifically, the relation between the different models and the number of states the device can hold are examined.

Paper Details

Date Published: 28 August 2010
PDF: 9 pages
Proc. SPIE 7818, Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II, 78180E (28 August 2010); doi: 10.1117/12.861513
Show Author Affiliations
Chris Yakopcic, Univ. of Dayton (United States)
Tarek M. Taha, Univ. of Dayton (United States)
Guru Subramanyam, Univ. of Dayton (United States)
Eunsung Shin, Univ. of Dayton (United States)
P. Terrence Murray, Univ. of Dayton (United States)
Stanley Rogers, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 7818:
Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II
Jean J. Dolne; Stanley Rogers; Thomas J. Karr; David P. Casasent; Victor L. Gamiz, Editor(s)

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