Publications:A Kernel based multi-resolution time series analysis for screening deficiencies in paper production

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Title A Kernel based multi-resolution time series analysis for screening deficiencies in paper production
Author
Year 2006
PublicationType Conference Paper
Journal
HostPublication Advances in neural networks - ISNN 2006 : third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006 ; proceedings. III
Conference third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006
DOI http://dx.doi.org/10.1007/11760191
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239221
Abstract

This paper is concerned with a multi-resolution tool for analysis of a time series aiming to detect abnormalities in various frequency regions. The task is treated as a kernel based novelty detection applied to a multi-level time series representation obtained from the discrete wavelet transform. Having a priori knowledge that the abnormalities manifest themselves in several frequency regions, a committee of detectors utilizing data dependent aggregation weights is build by combining outputs of detectors operating in those regions.