Authors: Gather, Ursula
Lanius, Vivian
Title: Robust online signal extraction from multivariate time series
Language (ISO): en
Abstract: We introduce robust regression-based online filters for multivariate time series and discuss their performance in real time signal extraction settings. We focus on methods that can deal with time series exhibiting patterns such as trends, level changes, outliers and a high level of noise as well as periods of a rather steady state. In particular, the data may be measured on a discrete scale which often occurs in practice. Our new filter is based on a robust two-step online procedure. We investigate its relevant properties and its performance by means of simulations and a medical application.
Subject Headings: Multivariate time series
Online methods
Robust regression
Signal extraction
URI: http://hdl.handle.net/2003/25862
http://dx.doi.org/10.17877/DE290R-12768
Issue Date: 2008-11-26T14:17:33Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

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