DocumentCode
59341
Title
Oscillator Array Models for Associative Memory and Pattern Recognition
Author
Maffezzoni, Paolo ; Bahr, Bichoy ; Zheng Zhang ; Daniel, Luca
Author_Institution
Politec. di Milano, Milan, Italy
Volume
62
Issue
6
fYear
2015
fDate
Jun-15
Firstpage
1591
Lastpage
1598
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.
Keywords
content-addressable storage; oscillators; pattern recognition; associative memory performance; device nonidealities; oscillator array models; pattern recognition; phase-domain modeling; resonant LC oscillators; simulation methodology; Arrays; Associative memory; Couplings; Numerical models; Oscillators; Pattern recognition; Synchronization; Associative memory; neurocomputing; oscillator array; phase-domain modeling;
fLanguage
English
Journal_Title
Circuits and Systems I: Regular Papers, IEEE Transactions on
Publisher
ieee
ISSN
1549-8328
Type
jour
DOI
10.1109/TCSI.2015.2418851
Filename
7105424
Link To Document