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Autoassociative Memory and Pattern Recognition in Micromechanical Oscillator Network

Kumar, Ankit and Mohanty, Pritiraj (2017) Autoassociative Memory and Pattern Recognition in Micromechanical Oscillator Network. Scientific Reports, 7 . Art. No. 411. ISSN 2045-2322. PMCID PMC5428492. doi:10.1038/s41598-017-00442-y.

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Towards practical realization of brain-inspired computing in a scalable physical system, we investigate a network of coupled micromechanical oscillators. We numerically simulate this array of all-to-all coupled nonlinear oscillators in the presence of stochasticity and demonstrate its ability to synchronize and store information in the relative phase differences at synchronization. Sensitivity of behavior to coupling strength, frequency distribution, nonlinearity strength, and noise amplitude is investigated. Our results demonstrate that neurocomputing in a physically realistic network of micromechanical oscillators with silicon-based fabrication process can be robust against noise sources and fabrication process variations. This opens up tantalizing prospects for hardware realization of a low-power brain-inspired computing architecture that captures complexity on a scalable manufacturing platform.

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Additional Information:© 2017 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit Received: 30 August 2016. Accepted: 28 February 2017. Published: 24 March 2017. We thank Farrukh Mateen and Joseph Boales for helpful discussions. We thank Diego Guerra for collaboration during the early part of the project. We also thank him for the experimental results demonstrating synchronization in a network of two coupled MEMS oscillators. These results served as the central motivation for the current study. Author Contributions: All authors designed the study, discussed the results, analyzed the data and prepared the manuscript. The authors declare that they have no competing interests.
PubMed Central ID:PMC5428492
Record Number:CaltechAUTHORS:20170403-141927394
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:75649
Deposited By: Tony Diaz
Deposited On:03 Apr 2017 21:29
Last Modified:28 Mar 2022 22:48

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