Please use this identifier to cite or link to this item: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/508
Title: Parameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniques
Authors: Jibia, Abdussamad U.
Salami, Momoh-Jimoh E.
Keywords: Terms—ARMA
Multiparameter
Multiexponential
Deconvolution
Issue Date: 1-Oct-2010
Publisher: IACSIT Press
Citation: Jibia, 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.
Abstract: Much 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.
URI: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/508
Appears in Collections:Research Articles



Items in EUSpace are protected by copyright, with all rights reserved, unless otherwise indicated.