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dc.contributor.authorTan, Berwin Rui Zhien_US
dc.identifier.citationTan, B. R. Z. (2022). Micromagnetic simulations for spin-based neuromorphic computing. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractAlthough modern A.I has enabled many new innovations such as voice assistant and facial recognitions, current A.I computers are still a long way from achieving human-like flexibility in problem solving and the ability to learn from unstructured stimuli with energy efficiency comparable to a human brain. Traditional von Neumann computers are highly inefficient at solving unstructured problems and as such, neuromorphic computers which mimic the biological neural network of a human brain have been researched extensively in a bid to create more powerful artificial neuromorphic computing systems that can compete with the human brain in unstructured problem-solving efficiency. Spin-based neuromorphic computing is a promising candidate that has the potential to create high-performance and low powered neuromorphic network. In our model, we make use of domain wall switching to model the Leaky-Integrate-and-Fire neurons. To further explore domain wall based neuromorphic computing, we ran simulations of our spin-based design to observe its Leaky-Integrate functionalities and analysed it suitability for use in neuromorphic computing.en_US
dc.publisherNanyang Technological Universityen_US
dc.titleMicromagnetic simulations for spin-based neuromorphic computingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorS.N. Piramanayagamen_US
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.description.degreeBachelor of Science in Applied Physicsen_US
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Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)
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