DOI: 10.7763/IJCTE.2012.V4.571
Parameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniques
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.
Index Terms—ARMA, multiparameter, multiexponential, deconvolution.
A. U. Jibia is with the Department of Electrical Engineering, Bayero University Kano, Nigeria (e-mail: ajumar@buk.edu.ng) .
M. E. Salami is with the Department of Mechatronics Engineering, International Islamic University Malaysia (e-mail: momoh@iium.edu.my).
Cite: Abdussamad U. Jibia and Momoh-Jimoh E. Salami, "Parameter Estimation of Transient Multiexponential Signals Using SVD-ARMA and Multiparameter Deconvolution Techniques," International Journal of Computer Theory and Engineering vol. 4, no. 5, pp. 751-757, 2012.