In supervised learning it is often all about labels. Do we have enough labeled data? If not,MEHR ERFAHREN
On the Behaviour of Permutation Entropy on Fractional Brownian Motion in a Multivariate Setting
Talk by Marisa Mohr at APSIPA 2020
The investigation of qualitative behaviour of the fractional Brownian motion is an important topic for modelling theoretic and real-world applications. Permutation Entropy is a robust and fast approach to quantify the complexity of a time series in a scalar-valued representation.
There are numerous studies on the behaviour of Permutation Entropy on fractional Brownian motion. Similarly, Multi-Scale Permutation Entropy is used to study structures on different time scales in a univariate context. Nevertheless, many real-world problems contain multivariate time series.
In this talk we investigate the behaviour of Permutation Entropy as well as the behaviour of Multi-Scale Permutation Entropy on fractional Brownian motion – each in the multivariate case.
Date: 9th December 2020
According to the Data Science Survey conducted by JetBrains in 2018, Jupyter/IPython notebooks are the most popularMEHR ERFAHREN