Oscillator Array Models for Associative Memory and Pattern Recognition
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Author(s)
Maffezzoni, Paolo
Bahr, Bichoy
Zhang, Zheng
Daniel, Luca
Date Issued
May 2015
Journal
IEEE Transactions on Circuits and Systems I: Regular Papers
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Maffezzoni, Paolo, Bichoy Bahr, Zheng Zhang, and Luca Daniel. “Oscillator Array Models for Associative Memory and Pattern Recognition.” IEEE Transactions on Circuits and Systems I: Regular Papers 62, no. 6 (June 2015): 1591–1598.
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Author's final manuscript
Abstract
Brain-inspired arrays of parallel processing oscillators represent an intriguing alternative to traditional computational methods for data analysis and recognition. This alternative is now becoming more concrete thanks to the advent of emerging oscillators fabrication technologies providing high density packaging and low power consumption. One challenging issue related to oscillator arrays is the large number of system parameters and the lack of efficient computational techniques for array simulation and performance verification. This paper provides a realistic phase-domain modeling and simulation methodology of oscillator arrays which is able to account for the relevant device nonidealities. The model is employed to investigate the associative memory performance of arrays composed of resonant LC oscillators.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/TCSI.2015.2418851
