Please use this identifier to cite or link to this item: http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/624
Title: Analysis of multicomponent transient signals using MUSIC superresolution technique
Authors: Jibia, Abdussamad U.
Salami, Momoh-Jimoh E.
Khalifa, Othman O.
Keywords: Transient analysis
Signal analysis
Multiple signal classification
Signal resolution
Magnetic analysis
Parameter estimation
Algorithm design and analysis
Biomedical engineering
Nuclear magnetic resonance
Medical diagnosis
Issue Date: 13-May-2008
Publisher: IEEE
Citation: Jibia, A. U., Salami, M. J. E., & Khalifa, O. O. (2008, May). Analysis of multicomponent transient signals using MUSIC superresolution technique. In 2008 International Conference on Computer and Communication Engineering (pp. 104-108). IEEE.
Abstract: The problem of estimating the parameters of transient signals consisting of real decay constants has for long been a subject of study by many researchers. Such signals arise in many problems in Science and Engineering like nuclear magnetic resonance for medical diagnosis, deep-level transient spectroscopy, fluorescence decay analysis, etc. Many techniques have been suggested by researchers to analyse these signals but they often produce mixed results. A new method of analysis using modified MUSIC (multiple signal classification) subspace algorithm is successfully applied to the analysis of this signal. A noisy multiexponential signal is subjected to a preprocessing procedure consisting of Gardenerspsila transformation and inverse filtering. Modified MUSIC algorithm is then applied to the deconvolved data. The parameters of focus in this paper are the number of components and decay constants. It is shown that with this technique parameter estimates do not significantly change with signal to noise ratio. The superiority of this algorithm over conventional MUSIC algorithm is also shown.
URI: 10.1109/ICCCE.2008.4580577
http://repository.elizadeuniversity.edu.ng/jspui/handle/20.500.12398/624
Appears in Collections:Research Articles

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