Sponsor
This work was supported by NSF grant CCF-1028378 and by the Air Force Office of Scientific Research (AFOSR) under MURI grant FA9550-12-1-0038, and by Spanish grant TEC2012-37868-C04-01(BIOSENSE) (with support from the European Regional Development Fund).
Published In
Frontiers in Neuroscience
Document Type
Article
Publication Date
12-24-2015
Subjects
Hopfield networks, Neural networks (Computer science), Electric circuits, Hybrid circuits, Memristors
Abstract
The purpose of this work was to demonstrate the feasibility of building recurrent artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memristor circuits. To do so, we modeled a Hopfield network implementing an analog-to-digital converter (ADC) with up to 8 bits of precision. Major shortcomings affecting the ADC's precision, such as the non-ideal behavior of CMOS circuitry and the specific limitations of memristors, were investigated and an effective solution was proposed, capitalizing on the in-field programmability of memristors. The theoretical work was validated experimentally by demonstrating the successful operation of a 4-bit ADC circuit implemented with discrete Pt/TiO2−x/Pt memristors and CMOS integrated circuit components.
DOI
10.3389/fnins.2015.00488
Persistent Identifier
http://archives.pdx.edu/ds/psu/16482
Citation Details
Guo, X., Merrikh-Bayat, F., Gao, L., Hoskins, B. D., Alibart, F., Linares-Barranco, B., … Strukov, D. B. (2015). Modeling and Experimental Demonstration of a Hopfield Network Analog-to-Digital Converter with Hybrid CMOS/Memristor Circuits. Frontiers in Neuroscience, 9, 488.
Description
Copyright © 2015 Guo, Merrikh-Bayat, Gao, Hoskins, Alibart, Linares-Barranco, Theogarajan, Teuscher and Strukov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.