Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158016
Title: Deep learning enabled invisibility cloak design
Authors: Yang, Chenbo
Keywords: Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Yang, C. (2022). Deep learning enabled invisibility cloak design. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158016
Project: W2443-212
Abstract: The invisibility cloak can be seen in numerous films and television shows; it is a fictitious device that can conceal the item inside it. The invisibility cloak has been a popular study issue in many sectors, particularly in the military such as stealth fighters. The transformation optics enables people to design new materials by using the coordinate transformation method to control the way of light propagation, thereby realizing invisibility. However, invisibility cloak based on this method performs poorly in describing the performance of the multilayered cloak in practical situations. In this project, the performance of a multilayered invisibility cloak will be modeled by Matlab and some deep learning based existing Matlab optimization tools will be used to optimize the model, in order to dim the intrinsic scatterings caused by discretization and simplification. In most instances, the optimized model not only has better performance, but also only requires a few layers, which is easy to implement in actual manufacturing.
URI: https://hdl.handle.net/10356/158016
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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