106 citations · 200 across the 11 of their papers we have counts for
11 papers
Formal Concept Lattice Representations and Algorithms for Hypergraphs
Michael G. Rawson, Audun Myers, Robert Green +2
There is increasing focus on analyzing data represented as hypergraphs, which are better able to express complex relationships amongst entities than are graphs. Much of the critica…
Topological Analysis of Temporal Hypergraphs
Audun Myers, Cliff Joslyn, Bill Kay +3
In this work we study the topological properties of temporal hypergraphs. Hypergraphs provide a higher dimensional generalization of a graph that is capable of capturing multi-way…
Persistent Homology of Coarse Grained State Space Networks
Audun D. Myers, Max M. Chumley, Firas A. Khasawneh +1
This work is dedicated to the topological analysis of complex transitional networks for dynamic state detection. Transitional networks are formed from time series data and they lev…
Temporal Network Analysis Using Zigzag Persistence
Audun Myers, David Muñoz, Firas Khasawneh +1
This work presents a framework for studying temporal networks using zigzag persistence, a tool from the field of Topological Data Analysis (TDA). The resulting approach is general…
Topological Signal Processing using the Weighted Ordinal Partition Network
Audun Myers, Firas A. Khasawneh, Elizabeth Munch
One of the most important problems arising in time series analysis is that of bifurcation, or change point detection. That is, given a collection of time series over a varying para…
ANAPT: Additive Noise Analysis for Persistence Thresholding
Audun D. Myers, Firas A. Khasawneh, Brittany T. Fasy
We introduce a novel method for Additive Noise Analysis for Persistence Thresholding (ANAPT) which separates significant features in the sublevel set persistence diagram of a time…
Dynamic State Analysis of a Driven Magnetic Pendulum using Ordinal Partition Networks and Topological Data Analysis
Audun Myers, Firas Khasawneh
The use of complex networks for time series analysis has recently shown to be useful as a tool for detecting dynamic state changes for a wide variety of applications. In this work,…
Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods
Joshua Tempelman, Audun Myers, Jeffrey Scruggs +1
The ability to characterize the state of dynamic systems has been a pertinent task in the time series analysis community. Traditional measures such as Lyapunov exponents are often…
On the Automatic Parameter Selection for Permutation Entropy
Audun Myers, Firas Khasawneh
Permutation Entropy (PE) has been shown to be a useful tool for time series analysis due to its low computational cost and noise robustness. This has drawn for its successful appli…
Delay Parameter Selection in Permutation Entropy Using Topological Data Analysis
Audun D. Myers, Max M. Chumley, Firas A. Khasawneh
Permutation Entropy (PE) is a powerful tool for quantifying the complexity of a signal which includes measuring the regularity of a time series. Additionally, outside of entropy an…
Persistent Homology of Complex Networks for Dynamic State Detection
Audun Myers, Elizabeth Munch, Firas A. Khasawneh
In this paper we develop a novel Topological Data Analysis (TDA) approach for studying graph representations of time series of dynamical systems. Specifically, we show how persiste…