Parameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniques

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dc.contributor.authorJibia, Abdussamad U.
dc.contributor.authorSalami, Momoh-Jimoh E.
dc.date.accessioned2019-08-14T15:17:26Z
dc.date.available2019-08-14T15:17:26Z
dc.date.issued2010-10-01
dc.description.abstractMuch has been reported about the analysis of transient multiexponentials data. In a previous paper, for example, this analysis was done using autoregressive moving average model which was applied to the deconvolved data arising from the application of Gardner transform followed by optimal compensation deconvolution to the original signal. Optimal compensation deconvolution uses a single parameter noise-reduction parameter. In this paper, a deconvolution parameter incorporating multiple noise-reduction parameters is used instead. Simulations and experimental results show that the proposed combination, despite its limitations supersedes several existing methods.en_US
dc.identifier.citationJibia, A. U., & Salami, M. J. E. (2012). Parameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniques. International Journal of Computer Theory and Engineering, 4(5), 751.en_US
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/508
dc.language.isoenen_US
dc.publisherIACSIT Pressen_US
dc.subjectTerms—ARMAen_US
dc.subjectMultiparameteren_US
dc.subjectMultiexponentialen_US
dc.subjectDeconvolutionen_US
dc.titleParameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniquesen_US
dc.typeArticleen_US
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