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Data compressive paradigm for spectral sensing and classification using electrically tunable detectors

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Bibliographic Details
Title:	Data compressive paradigm for spectral sensing and classification using electrically tunable detectors
Authors:	Jang, Woo-Yong
Committee Members:	Hayat, Majeed; Krishna, Sanjay; Brueck, Steven; Prasad, Sudhakar; Zarkesh-Ha, Payman
Summary:	This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; (2) further demonstration of the spectral-classification capability of tunable DWELL IR focal-plane array (FPA), again without using any spectral filters; and (3) development of a generalized filter-free data-compressive spectral sensing paradigm using the DWELL detector that enables arbitrarily specified MS sensing (e.g., spectral matched filtering, slope sensing, multicolor sensing, etc.) without using any spectral filters and possibly under constrained acquisition times.
URL:	https://digitalrepository.unm.edu/ece_etds/124
Database:	OpenDissertations

Description
Abstract:	This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; (2) further demonstration of the spectral-classification capability of tunable DWELL IR focal-plane array (FPA), again without using any spectral filters; and (3) development of a generalized filter-free data-compressive spectral sensing paradigm using the DWELL detector that enables arbitrarily specified MS sensing (e.g., spectral matched filtering, slope sensing, multicolor sensing, etc.) without using any spectral filters and possibly under constrained acquisition times.