BYU

Abstract by William Wright

Personal Infomation


Presenter's Name

William Wright

Degree Level

Undergraduate

Abstract Infomation


Department

Mathematics

Faculty Advisor

Gregory Conner

Title

Coordinated Persistent Homology in Analysis of Avian Vocalizations

Abstract

In recent years, many new data analysis algorithms have been developed that employ Persistent Homology to extract previously unobtainable patterns from data. However, Persistent Homology algorithms are limited in their usefulness because they can only analyze one parameter at a time. Other algorithms have been developed in to analyze multiple parameters at once (these are referred to as Multiple Persistent Homology algorithms), but as it turns out they are not feasibly computable given any realistic data set. Here we employ a compromise technique (know as Coordinated Persistent Homology) developed by Nick Callor and Gregory Conner at BYU to analyze avian vocalizations in an attempt to differentiate between spiecies.