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Machine learning of SVM classification utilizing complete binary tree structure for PAM-4/8 optical interconnection

  • Guoyao Chen
  • , Lin Sun
  • , Ke Xu
  • , Jiangbing Du
  • , Zuyuan He

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A machine learning method of effective nonlinear decision frame for PAM-N system based on support vector machine (SVM) using complete binary tree (CBT) structure is demonstrated in this work. The simulations results indicate improved performance by the proposed classifier which enhances the power sensitivity by 2-dB and 6-dB at the receiver side in 100-Gbps PAM-4 and PAM-8 systems respectively.

Original languageEnglish
Title of host publication6th IEEE Photonics Society Optical Interconnects Conference, OI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages47-48
Number of pages2
ISBN (Electronic)9781509050154
DOIs
StatePublished - 30 Jun 2017
Externally publishedYes
Event6th IEEE Photonics Society Optical Interconnects Conference, OI 2017 - Santa Fe, United States
Duration: 5 Jun 20177 Jun 2017

Publication series

Name6th IEEE Photonics Society Optical Interconnects Conference, OI 2017

Conference

Conference6th IEEE Photonics Society Optical Interconnects Conference, OI 2017
Country/TerritoryUnited States
CitySanta Fe
Period5/06/177/06/17

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