Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data

This paper proposes a hierarchical feature extractor for non-stationary streaming time series based on the concept of switching observable Markov chain models. The slow time-scale non-stationary behaviors are considered to be a mixture of quasi-stationary fast time-scale segments that are exhibited...

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Veröffentlicht in:	arXiv.org 2017-02
Hauptverfasser:	Adedotun Akintayo, Sarkar, Soumik
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Change detection Complexity Computer simulation Dirichlet problem Dynamical systems Feature extraction Filtration Markov analysis Markov chains Nonlinear dynamics Nonlinear systems Real time operation Time series Uniqueness
Online-Zugang:	Volltext
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