國立虎尾科技大學 |

Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems // Cindy Hsin Pan.
Author:	Pan, Cindy Hsin,
Description:	1 electronic resource (69 pages)
Notes:	Source: Masters Abstracts International, Volume: 86-08.
Contained By:	Masters Abstracts International86-08.
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31765734
ISBN:	9798302875525

Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems /
Pan, Cindy Hsin,

Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems /Cindy Hsin Pan. - 1 electronic resource (69 pages)

Source: Masters Abstracts International, Volume: 86-08.

Advances in metasurface inverse design have the potential to revolutionize intelligent sensing and imaging systems by leveraging computational optimization and machine learning. This thesis presents a unified exploration of physics-informed optimization techniques applied across three distinct works, each addressing a critical aspect of modern engineering challenges. Specifically, we explore the inverse design of metasurfaces, from the RF domain to the visible range, uniting the fields of wireless communication and optical imaging. Chapter 2 introduces a novel approach to the inverse design of GHz reconfigurable antennas using physics-informed graph neural networks, enabling intelligent beam-forming. Chapter 3 delves into the optimization of a multilayer broadband metalens for dual-functional color-sorting and polarization imaging, demonstrating significant improvements in optical efficiency and functionality. And Chapter 4 transitions to high resolution 3D imaging, presenting a neural single-shot GHz FMCW correlation imaging system that achieves absolute depth reconstruction with high precision. Together, these works illustrate the versatility and impact of physics-informed optimization, uniting computational design and physics priors to push the boundaries of metasurface technologies and beyond.

English

ISBN: 9798302875525Subjects--Topical Terms:

596380
Electrical engineering.
Subjects--Index Terms:

Inverse-design

Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems /
LDR:02759nam a22004333i 4500 001 1157889
005 20250603111436.5
006 m o d
007 cr|nu||||||||
008 250804s2025 miu||||||m |||||||eng d
020 $a 9798302875525
035 $a (MiAaPQD)AAI31765734
035 $a AAI31765734
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Pan, Cindy Hsin, $e author. $3 1484179
245 1 0 $a Physics-Informed Optimization Methods of Metasurface and Reconfigurable Antenna Inverse Design for Intelligent Sensing and Imaging Systems / $c Cindy Hsin Pan.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2025
300 $a 1 electronic resource (69 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 86-08.
500 $a Advisors: Sturm, James C.
502 $b M.S.E. $c Princeton University $d 2025.
520 $a Advances in metasurface inverse design have the potential to revolutionize intelligent sensing and imaging systems by leveraging computational optimization and machine learning. This thesis presents a unified exploration of physics-informed optimization techniques applied across three distinct works, each addressing a critical aspect of modern engineering challenges. Specifically, we explore the inverse design of metasurfaces, from the RF domain to the visible range, uniting the fields of wireless communication and optical imaging. Chapter 2 introduces a novel approach to the inverse design of GHz reconfigurable antennas using physics-informed graph neural networks, enabling intelligent beam-forming. Chapter 3 delves into the optimization of a multilayer broadband metalens for dual-functional color-sorting and polarization imaging, demonstrating significant improvements in optical efficiency and functionality. And Chapter 4 transitions to high resolution 3D imaging, presenting a neural single-shot GHz FMCW correlation imaging system that achieves absolute depth reconstruction with high precision. Together, these works illustrate the versatility and impact of physics-informed optimization, uniting computational design and physics priors to push the boundaries of metasurface technologies and beyond.
546 $a English
590 $a School code: 0181
650 4 $a Electrical engineering. $3 596380
650 4 $a Engineering. $3 561152
650 4 $a Medical imaging. $3 1180167
653 $a Inverse-design
653 $a Machine learning
653 $a Metasurface
653 $a Imaging systems
653 $a Polarization imaging
690 $a 0544
690 $a 0574
690 $a 0537
710 2 $a Princeton University. $b Electrical and Computer Engineering. $3 1413580
720 1 $a Sturm, James C. $e degree supervisor.
773 0 $t Masters Abstracts International $g 86-08.
790 $a 0181
791 $a M.S.E.
792 $a 2025
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31765734