Computing with Memristor Networks

dc.contributor.authorBennett, Christopher H.
dc.contributor.authorKonkoli, Zoran
dc.contributor.departmentChalmers tekniska högskola / Externsv
dc.contributor.departmentChalmers University of Technology / Externalen
dc.date.accessioned2019-07-03T13:40:19Z
dc.date.available2019-07-03T13:40:19Z
dc.date.issued2014
dc.description.abstractIt has been suggested that CMOS technologies will hit scaling limits due to fundamental design issues at the regime of molecular electronics. In this project, the memristor device has been evaluated as a candidate for building high-density, high-performance computers at such a scale. Although memristors are already under active research and development as random access memory, in this project, we evaluate their potential for neuromorphic (brain-inspired) information processing in the context of reservoir computing. We quantify a memristor network's capability to analyze sets of time-dependent input data for pattern recognition applications. We pose the following key question: given a network of a certain design, which signals might it be particularly adept at recognizing? To answer that question, a rigorous mathematical approach has been developed and implemented as computer software. Our preliminary results indicate that the conceptual approach that has been developed can be used to answer this question, and suggest that memristor networks are capable of real-time pattern recognition.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/218659
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectGrundläggande vetenskaper
dc.subjectAnnan data- och informationsvetenskap
dc.subjectHållbar utveckling
dc.subjectInformations- och kommunikationsteknik
dc.subjectNanovetenskap och nanoteknik
dc.subjectBasic Sciences
dc.subjectOther Computer and Information Science
dc.subjectSustainable Development
dc.subjectInformation & Communication Technology
dc.subjectNanoscience & Nanotechnology
dc.titleComputing with Memristor Networks
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeNanotechnology (MPNAT), MSc
Ladda ner