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Diffractive Integrated Photonics for Analog Computing and Machine Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Diffractive Integrated Photonics for Analog Computing and Machine Learning./
Author:	Wang, Zi.
Description:	1 online resource (95 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-03, Section: B.
Contained By:	Dissertations Abstracts International84-03B.
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29258573click for full text (PQDT)
ISBN:	9798351461434

Diffractive Integrated Photonics for Analog Computing and Machine Learning.
Wang, Zi.

Diffractive Integrated Photonics for Analog Computing and Machine Learning. - 1 online resource (95 pages)

Source: Dissertations Abstracts International, Volume: 84-03, Section: B.

Thesis (Ph.D.)--University of Delaware, 2022.

Includes bibliographical references

Recently, optical analog signal processing draws a lot of attentions due to the rising of deep learning, and integrated photonics is a promising platform. In this thesis, the author propose a design method combining the metasurface with the integrated photonics, and demonstrate the analog computing and machine learning meta-systems. The author demonstrate both forward and inversely design methods for different applications: spatial differentiation, pattern classification and wavelength demultiplexing. Compared with free-space optical systems, the proposed on-chip meta-system allows more compact footprint and better mechanical robustness.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798351461434Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

Integrated photonicsIndex Terms--Genre/Form:

542853
Electronic books.

Diffractive Integrated Photonics for Analog Computing and Machine Learning.
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500 $a Source: Dissertations Abstracts International, Volume: 84-03, Section: B.
500 $a Advisor: Gu, Tingyi.
502 $a Thesis (Ph.D.)--University of Delaware, 2022.
504 $a Includes bibliographical references
520 $a Recently, optical analog signal processing draws a lot of attentions due to the rising of deep learning, and integrated photonics is a promising platform. In this thesis, the author propose a design method combining the metasurface with the integrated photonics, and demonstrate the analog computing and machine learning meta-systems. The author demonstrate both forward and inversely design methods for different applications: spatial differentiation, pattern classification and wavelength demultiplexing. Compared with free-space optical systems, the proposed on-chip meta-system allows more compact footprint and better mechanical robustness.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 649834
653 $a Integrated photonics
653 $a Machine learning
653 $a Metasurface
653 $a Spatial differentiation
653 $a Wavelength demultiplexing
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690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a University of Delaware. $b Electrical and Computer Engineering. $3 3183620
773 0 $t Dissertations Abstracts International $g 84-03B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29258573 $z click for full text (PQDT)