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University of Illinois at Urbana-Champaign

Machine learning approach for cascade-able nonlinear transceiver modeling and high speed link simulation

dc:creator Zhao, Yixuan

thesis:degree_name Ph.D.

dc:date2022

Abstract

dc:description

Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01

Degree

thesis:*

Name thesis:degree_name: Ph.D.
Level thesis:degree_level: Dissertation
Discipline thesis:degree_discipline: Electrical & Computer Engr
Grantor: University of Illinois at Urbana-Champaign
Year dc:date: 2022

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Zhao, Yixuan
Contributors dc:contributor: Schutt-Aine, Jose E
Kudeki, Erhan
Bernhard, Jennifer T
Dragic, Peter D

Subjects

dc:subject × 6

Rights

dc:rights

Statement dc:rights: Copyright 2022 Yixuan Zhao
Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: https://hdl.handle.net/2142/117653
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/117653

Chain of custody

source

Harvested from: University of Illinois - Urbana-Champaign
Base URL: www.ideals.illinois.edu/oai-pmh
Last updated: 2026-07-22
Source record: OAI-PMH GetRecord

related terms

citation

Zhao, Yixuan. Machine learning approach for cascade-able nonlinear transceiver modeling and high speed link simulation. Dissertation thesis, University of Illinois at Urbana-Champaign, 2022. https://hdl.handle.net/2142/117653

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