A tunable neural network based decision feed-back equalizer model for high-speed link simulation

Thong Nguyen, Jose Schutt-Aine

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

Abstract

This paper presents a model combining a feedforward neural network (FNN) with a recurrent neural network (RNN) to model Decision Feed-back Equalizer (DFE). By using the FNN as the mapping between the tap values and the dynamic behavior of the DFE, a complete model of the DFE can be constructed for channel simulation. The paper shows a 2-tap DFE example in which excellent agreement between the model generated by the proposed method and transient simulation can be observed.

Original languageEnglish (US)
Title of host publicationEPEPS 2020 - IEEE 29th Conference on Electrical Performance of Electronic Packaging and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728161617
DOIs
StatePublished - Oct 2020
Externally publishedYes
Event29th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2020 - San Jose, United States
Duration: Oct 5 2020Oct 7 2020

Publication series

NameEPEPS 2020 - IEEE 29th Conference on Electrical Performance of Electronic Packaging and Systems

Conference

Conference29th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2020
Country/TerritoryUnited States
CitySan Jose
Period10/5/2010/7/20

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Energy Engineering and Power Technology

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