Classification of non‐stationary time series

Krzemieniewska, Karolina and Eckley, Idris and Fearnhead, Paul (2014) Classification of non‐stationary time series. Stat, 3 (1). pp. 144-157. ISSN 2049-1573

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Abstract

In this paper we consider the problem of classifying non-stationary time series. The method that we introduce is based on the locally stationary wavelet paradigm and seeks to take account of the fact that there may be within-class variation in the signals being analysed. Specifically, we seek to identify the most stable spectral coefficients within each training group and use these to classify a new, previously unseen, time series. In both simulated examples and an aerosol spray example provided by an industrial collaborator, our approach is found to yield superior classification performance when compared against the current state of the art.

Item Type:
Journal Article
Journal or Publication Title:
Stat
Subjects:
ID Code:
70657
Deposited By:
Deposited On:
04 Sep 2014 11:15
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 08:58