Detection of locally stationary segments in time series: Algorithms and applications
Uwe Ligges, Claus Weihs, Petra Hasse-Becker · RePEc: Research Papers in Economics · 2002
In many applications it is required to segment a time series into its locally stationary parts.Two applications are presented: As a rst example consider online monitoring of a BTA Deep-Hole-Drilling process.Here chattering and spiralling of the drilling tool should be avoided by process control.A second example is the analysis of vocal sound signals.It may be required to analyze only speci c tones instead of a whole song.Three new algorithms are introduced in this paper, all based on the theory of Dahlhaus (1997) and the analysis of the spectrum of time series, but with dierent methods to distinguish locally stationary parts of the signals.