On the design of phase locked loop oscillatory neural networks: Mitigation of transmission delay effects

Rongye Shi, Thomas C. Jackson, Brian Swenson, Soummya Kar, Lawrence Pileggi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper introduces a novel design of phase locked loop (PLL) based oscillatory neural networks (ONNs) to mitigate the frequency clustering phenomenon caused by transmission delays in real systems. Theoretical analysis of the ONN reveals that transmission delays can produce frequency clustering that leads to synchronization and convergence failure. This paper describes the redesign of ONN dynamics and associated system-level architecture to achieve robustness. Specifically, we first demonstrate that using the phase information of zero-crossing points of inputs as the PLL error signal enables the ONN dynamical model to correctly synchronize under uniform transmission delays. A Type-II PLL based ONN architecture is shown via simulation to provide this property in hardware. Furthermore, to accommodate non-uniform transmission delays in hardware, a phase synchronization technique is proposed that is shown to provide the correct synchronization behavior.

Original languageEnglish (US)
Title of host publication2016 International Joint Conference on Neural Networks, IJCNN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2039-2046
Number of pages8
ISBN (Electronic)9781509006199
DOIs
StatePublished - Oct 31 2016
Event2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
Duration: Jul 24 2016Jul 29 2016

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2016-October

Other

Other2016 International Joint Conference on Neural Networks, IJCNN 2016
Country/TerritoryCanada
CityVancouver
Period7/24/167/29/16

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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