Background Automatic detection or classification of adventitious sounds is useful to assist
physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive …

The goal of this paper is to establish the fundamental tools to analyze signals defined over a
topological space, ie a set of points along with a set of neighborhood relations. This setup …

We explore the evolution of daily returns of four major US stock market indices during the
technology crash of 2000, and the financial crisis of 2007–2009. Our methodology is based …

Topological data analysis (TDA) is a collection of powerful tools that can quantify shape and
structure in data in order to answer questions from the data's domain. This is done by …

Digital respiratory sounds provide valuable information for telemedicine and smart diagnosis
in an non-invasive way of pathological detection. As the typical continuous abnormal …

This work introduces a new dataset and framework for the exploration of topological data
analysis (TDA) techniques applied to time-series data. We examine the end-to-end TDA …

This paper describes a new approach for ascertaining the stability of stochastic dynamical
systems in their parameter space by examining their time series using topological data …

In this work, respiratory sounds are classified into four classes in the presence of various
noises (talking, coughing, motion artefacts, heart and intestinal sounds) using support vector …

In this paper we develop an alternative topological data analysis (TDA) approach for
studying graph representations of time series of dynamical systems. Specifically, we show …

Topological data analysis (TDA) uses information from topological structures in complex
data for statistical analysis and learning. This paper discusses persistent homology, a part of …