Time series signal recovery methods: Comparative study

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dc.contributor.authorKamalov, Firuz
dc.contributor.authorSulieman, Hana
dc.date.accessioned2022-05-18T13:47:07Z
dc.date.available2022-05-18T13:47:07Z
dc.date.copyright© 2021
dc.date.issued2021
dc.descriptionThis conference paper is not available at CUD collection. The version of scholarly record of this paper is published in 2021 International Symposium on Networks, Computers and Communications (ISNCC) (2021), available online at: https://doi.org/10.1109/ISNCC52172.2021.9615669
dc.description.abstractSignal data often contains missing values. Effective replacement (imputation) of the missing values can have significant positive effects on processing the signal. In this paper, we compare three commonly employed methods for estimating missing values in time series data: forward fill, backward fill, and mean fill. We carry out a large scale experimental analysis using 3, 600 AR(1)-based simulated time series to determine the optimal method for estimating missing values. The results of the numerical experiments show that the forward and backward fill methods are better suited for times series with large positive correlations, while the mean fill method is better suited for times series with low or negative correlations. The extensive and exhaustive nature of the numerical experiments provides a definitive answer to the comparison of the three imputation methods. © 2021 IEEE.
dc.identifier.citationKamalov, F., & Sulieman, H. (2021). Time series signal recovery methods: Comparative study. 2021 International Symposium on Networks, Computers and Communications (ISNCC). https://doi.org/10.1109/ISNCC52172.2021.9615669
dc.identifier.isbn978-073811316-6
dc.identifier.urihttps://doi.org/10.1109/ISNCC52172.2021.9615669
dc.identifier.urihttp://hdl.handle.net/20.500.12519/642
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relationKamalov, F., Canadian University Dubai, Department Of Electrical Engineering, Dubai, United Arab Emirates; Sulieman, H., American University Of Sharjah, Department Of Mathematics And Statistics, Sharjah, United Arab Emirates
dc.relation.ispartofseries2021 International Symposium on Networks, Computers and Communications (ISNCC)
dc.rightsPermission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc.
dc.rights.holderCopyright : © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.urihttps://www.ieee.org/publications/rights/rights-policies.html
dc.subjectAR
dc.subjectAutoregression
dc.subjectFilling methods
dc.subjectImputation
dc.subjectPACF
dc.subjectTime series
dc.titleTime series signal recovery methods: Comparative study
dc.typeConference Paper
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