Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163566
Title: Deep learning enabled invisibility cloak design
Authors: Eng, Clifford Ping Hao
Keywords: Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Eng, C. P. H. (2022). Deep learning enabled invisibility cloak design. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/163566
Project: A2312-212
Abstract: Invisibility cloak has become a hot topic recently, and development has been working on it. In this project, approach is made to reduce scattering of invisibility cloak using optimization and deep leaning techniques. Two different approaches were experimented in this project, first one was using Optimization Toolbox optimized parameters to train a MLP model. The second one was by using Global Optimization Toolbox’s MultiStart solver to optimize parameters. After analyzing, the second one yields a better performance which resulted in lower scattering energy, with the only downside of longer computation time.
URI: https://hdl.handle.net/10356/163566
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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