Noise-Resilient Photonic Analog Neural Networks

dc.contributor.author	Agnihotri, Apoorv
dc.date.accessioned	2025-05-06T10:38:13Z
dc.date.available	2025-05-06T10:38:13Z
dc.date.issued	2024
dc.identifier.issn	0733-8724
dc.identifier.uri	http://hdl.handle.net/10900/165202
dc.language.iso	en	de_DE
dc.publisher	Piscataway : IEEE - Inst Electrical Electronics Engineers Inc	de_DE
dc.relation.uri	http://dx.doi.org/10.1109/JLT.2024.3433454	de_DE
dc.subject.ddc	530	de_DE
dc.subject.ddc	600	de_DE
dc.title	Noise-Resilient Photonic Analog Neural Networks	de_DE
dc.type	Article	de_DE
utue.quellen.id	20250203000000_00470
utue.publikation.seiten	7969-7976	de_DE
utue.personen.roh	Varri, Akhil
utue.personen.roh	Brueckerhoff-Plueckelmann, Frank
utue.personen.roh	Dijkstra, Jelle
utue.personen.roh	Wendland, Daniel
utue.personen.roh	Bankwitz, Rasmus
utue.personen.roh	Agnihotri, Apoorv
utue.personen.roh	Pernice, Wolfram H. P.
dcterms.isPartOf.ZSTitelID	Journal of Lightwave Technology	de_DE
dcterms.isPartOf.ZS-Issue	22	de_DE
dcterms.isPartOf.ZS-Volume	42	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE