Improving the components independence of decomposition in time series data
This paper addresses the weakness of ensemble empirical mode decomposition approach in extracting the components of a time series signal data. In general, this approach provides non-independent component. The existing approach using cluster analysis provided an improvement yet not perfect. We the...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
University of Allahabad
2015
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Online Access: | http://psasir.upm.edu.my/id/eprint/45092/1/TIME.pdf |
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author | Wijayanto, Hari Sartono, Bagus Fitrianto, Anwar Nursyifa, Casia |
author_facet | Wijayanto, Hari Sartono, Bagus Fitrianto, Anwar Nursyifa, Casia |
author_sort | Wijayanto, Hari |
collection | UPM |
description | This paper addresses the weakness of ensemble empirical mode
decomposition approach in extracting the components of a time series
signal data. In general, this approach provides non-independent
component. The existing approach using cluster analysis provided an improvement yet not perfect. We then do a modification to reach
components with two main characteristics. First, the components
should reflect the true patterns. Second, the components are
independent among the others as much as possible. By a small
empirical study, we observe the modification we propose produces
better results than the existing approaches. |
first_indexed | 2024-03-06T08:58:25Z |
format | Article |
id | upm.eprints-45092 |
institution | Universiti Putra Malaysia |
language | English |
last_indexed | 2024-03-06T08:58:25Z |
publishDate | 2015 |
publisher | University of Allahabad |
record_format | dspace |
spelling | upm.eprints-450922021-04-18T00:26:58Z http://psasir.upm.edu.my/id/eprint/45092/ Improving the components independence of decomposition in time series data Wijayanto, Hari Sartono, Bagus Fitrianto, Anwar Nursyifa, Casia This paper addresses the weakness of ensemble empirical mode decomposition approach in extracting the components of a time series signal data. In general, this approach provides non-independent component. The existing approach using cluster analysis provided an improvement yet not perfect. We then do a modification to reach components with two main characteristics. First, the components should reflect the true patterns. Second, the components are independent among the others as much as possible. By a small empirical study, we observe the modification we propose produces better results than the existing approaches. University of Allahabad 2015-02 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/45092/1/TIME.pdf Wijayanto, Hari and Sartono, Bagus and Fitrianto, Anwar and Nursyifa, Casia (2015) Improving the components independence of decomposition in time series data. Far East Journal of Mathematical Sciences, 96 (3). pp. 303-314. ISSN 0972-0871 http://www.pphmj.com/abstract/8928.htm 10.17654/FJMSFeb2015_303_314 |
spellingShingle | Wijayanto, Hari Sartono, Bagus Fitrianto, Anwar Nursyifa, Casia Improving the components independence of decomposition in time series data |
title | Improving the components independence of decomposition in time series data |
title_full | Improving the components independence of decomposition in time series data |
title_fullStr | Improving the components independence of decomposition in time series data |
title_full_unstemmed | Improving the components independence of decomposition in time series data |
title_short | Improving the components independence of decomposition in time series data |
title_sort | improving the components independence of decomposition in time series data |
url | http://psasir.upm.edu.my/id/eprint/45092/1/TIME.pdf |
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