School of Mathematical Sciences

Detection of changes in the generating mechanism of time series via the epsilon-complexity of continuous functions menu

Detection of changes in the generating mechanism of time series via the epsilon-complexity of continuous functions

Speaker: 
Alexandra Piryatinska, Department of Mathematics, San Francisco State University
Date/Time: 
Tue, 17/12/2013 - 16:30
Room: 
M203
Seminar series: 

A novel methodology for the detection of abrupt changes in the generating mechanisms (stochastic, deterministic or mixed) of a time series, without any prior knowledge about them, will be presented. This methodology has two components: the first is a novel concept of the epsilon-complexity, and the second is a method for the change point detection. In the talk, we will give the definition of the epsilon-complexity of a continuous function defined on a compact segment. We will show that for the Holder class of functions there exists an effective characterization of the epsilon-complexity. The results of simulations and applications to the electroencephalogram data and financial time series will be presented. (The talk is based on joint work with Boris Darkhovsky at the Russian Academy of Sciences.)