Nonlinear Methods Most Applied to Heart-Rate Time Series: A Review

A Review of Machine Learning Applied to Medical Time Series

The field of medicine has witnessed numerous improvements in recent decades, yet many of the biological processes underlying the medical problems faced today remain a mystery. Recent advances in machine learning enable the extraction of features that would be nearly impossible for experts to find in the massive medical datasets. The techniques not only offer improved continuous patient monitori...

Time Series Data Mining Methods: A Review

Today, real world time series data sets can take a size up to a trillion observations and even more. Data miners’ task is it to detect new information that is hidden in this massive amount of data. While well known techniques for data mining in cross sections have been developed, time series data mining methods are not as sophisticated and established yet. Large time series bring along problems...

Interdisciplinary application of nonlinear time series methods

This paper reports on the application to field measurements of time series methods developed on the basis of the theory of deterministic chaos. The major difficulties are pointed out that arise when the data cannot be assumed to be purely deterministic and the potential that remains in this situation is discussed. For signals with weakly nonlinear structure, the presence of nonlinearity in a ge...

Nonlinear Time Series: Nonparametric and Parametric Methods

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran