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University of Illinois at Urbana-Champaign

Sampling, non-linearities and scales: rethinking convolutional neural networks from a signal processing perspective

dc:creator Chaman, Anadi

thesis:degree_name Ph.D.

dc:date2024

Abstract

dc:description

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms

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: 2024

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Chaman, Anadi
Contributors dc:contributor: Dokmanić, Ivan
Bresler, Yoram
Weiss, Yair
Zhao, Zhizhen

Subjects

dc:subject × 7

Rights

dc:rights

Statement dc:rights: Copyright 2024 Anadi Chaman
Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: https://hdl.handle.net/2142/125624
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/125624

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

Chaman, Anadi. Sampling, non-linearities and scales: rethinking convolutional neural networks from a signal processing perspective. Dissertation thesis, University of Illinois at Urbana-Champaign, 2024. https://hdl.handle.net/2142/125624

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