PREDICTIVE MODELLING OF STT-MRAM THROUGH ARTIFICAL NEURAL NETWORK

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DC Field	Value	Language
dc.contributor.author	Saini, Vaibhav	-
dc.date.accessioned	2025-12-17T07:02:41Z	-
dc.date.available	2025-12-17T07:02:41Z	-
dc.date.issued	2024-06	-
dc.identifier.uri	http://localhost:8081/jspui/handle/123456789/18494	-
dc.guide	Dasgupta, Avirup	en_US
dc.description.abstract	An STT-MRAM memory array's individual cells must fulfil certain performance requirements to function reliably. The basic physical concepts of STT-MRAM are reviewed and some of these needs are described. In this study we are trying to analyze the effect of various parameter on magnetization and trying to model it with machine learning model with the comparison of natural way of finding the magnetization of stt-mram cell through llg equation.	en_US
dc.language.iso	en	en_US
dc.publisher	IIT, Roorkee	en_US
dc.title	PREDICTIVE MODELLING OF STT-MRAM THROUGH ARTIFICAL NEURAL NETWORK	en_US
dc.type	Dissertations	en_US
Appears in Collections:	MASTERS' THESES (E & C)

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