Degree Type
Dissertation
Date of Award
2009
Degree Name
Doctor of Philosophy
Department
Statistics
First Advisor
Stephen Vardeman
Second Advisor
Max Morris
Abstract
This thesis focuses on applying statistical methods to spectral-temporal data obtained from point source events. This work arises from the need in some military and national defense applications to quickly detect, locate, and identify short duration "energetic" electromagnetic events providing particular characteristic patterns of evolution over time. The first article discusses model building for spectral-temporal data that have complete spectral and temporal information over an event's evolution. The goal of this work was to build models to serve as the basis for algorithms that can be used to distinguish between different types of electromagnetic events in real time.
The second article discusses the preliminary design of an algorithm for real-time discrimination between different types of point source events based on spectral-temporal data. The development of the algorithm was based on data obtained from 3 classes of safety matches and from simulated data based on fitted models developed in the first article.
The third and final article discusses important pratical considerations regarding the sensor and experimental set-up used in the previous two articles. If this line of inquiry is to be further developed, this article discusses some practical considerations that should be addressed when moving forward.
DOI
https://doi.org/10.31274/etd-180810-897
Copyright Owner
Monica Marie Reising
Copyright Date
2009
Language
en
Date Available
2012-04-30
File Format
application/pdf
File Size
104 pages
Recommended Citation
Reising, Monica Marie, "Modeling and discrimination for spectral-temporal data" (2009). Graduate Theses and Dissertations. 11901.
https://lib.dr.iastate.edu/etd/11901
