Sensor Modeling with a focus on noise modeling in the context of Self-Driving Vehicles using Neural Network

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dc.contributor.authorEsmi Serkani, Siamak
dc.contributor.departmentChalmers tekniska högskola / Institutionen för fysik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Physics (Chalmers)en
dc.date.accessioned2019-07-03T14:27:36Z
dc.date.available2019-07-03T14:27:36Z
dc.date.issued2016
dc.description.abstractSystem Simulation has become an indistinct part of developments in which there are complexity involved. In this thesis, modeling of one of the most applicable sensors in automotive industry is carried out by applying a machine learning method known as neural networks. This report outlines a method of employing a combination of neural network techniques to model system behaviour; an applicable method compatible with any type of data. By integrating this sensor model into simulation environment (OpenDaVINCI), simulation test which plays an important role in testing of selfdriving vehicles will become more realistic.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/249358
dc.language.isoeng
dc.setspec.uppsokPhysicsChemistryMaths
dc.subjectBuilding Futures
dc.subjectGrundläggande vetenskaper
dc.subjectHållbar utveckling
dc.subjectInnovation och entreprenörskap (nyttiggörande)
dc.subjectAnnan teknik
dc.subjectBuilding Futures
dc.subjectBasic Sciences
dc.subjectSustainable Development
dc.subjectInnovation & Entrepreneurship
dc.subjectOther Engineering and Technologies
dc.titleSensor Modeling with a focus on noise modeling in the context of Self-Driving Vehicles using Neural Network
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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