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 :
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