Back to results
University of New Mexico
Data compressive paradigm for spectral sensing and classification using electrically tunable detectors
Abstract
dc:description.abstractThis 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.
Degree
thesis:*- Name thesis:degree_name
- Computer Engineering
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Electrical and Computer Engineering
- Year
- 2013
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Jang, Woo-Yong
- Contributors dc:contributor
-
- Hayat, Majeed
- Krishna, Sanjay
- Brueck, Steven
- Prasad, Sudhakar
- Zarkesh-Ha, Payman
Subjects
dc:subject × 4Rights
- Language dc:language
- English
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://digitalrepository.unm.edu/ece_etds/124
- OAI identifier oai:identifier
- oai:digitalrepository.unm.edu:ece_etds-1123