Analysing time series structure with hidden Markov models

Author

Azzouzi, Mehdi ; Nabney, Ian T.

Author_Institution

Neural Comput. Res. Group, Aston Univ., Birmingham, UK

fYear

1998

fDate

31 Aug-2 Sep 1998

Firstpage

402

Lastpage

408

Abstract

Considers the problem of extracting the relationships between two time series in a non-linear non-stationary environment with hidden Markov models (HMMs). We describe an algorithm which is capable of identifying associations between variables. The method is applied both to synthetic data and real data. We show that HMMs are capable of modelling the oil drilling process and that they outperform existing methods

Keywords

hidden Markov models; pattern recognition; time series; hidden Markov models; nonlinear nonstationary environment; oil drilling process; synthetic data; time series structure; Character generation; Data mining; Fluctuations; Hidden Markov models; Monitoring; Oil drilling; Petroleum; Random variables; Time series analysis; Tin;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop

Conference_Location

Cambridge

ISSN

1089-3555

Print_ISBN

0-7803-5060-X

Type

conf

DOI

10.1109/NNSP.1998.710670

Filename

710670

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2671662