Performance evaluation of the deconvolution techniques used in analyzing multicomponent transient signals

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dc.contributor.authorSalami, Momoh-Jimoh E.
dc.contributor.authorSidek, S. N.
dc.date.accessioned2019-08-14T15:09:52Z
dc.date.available2019-08-14T15:09:52Z
dc.date.issued2000-09-24
dc.description.abstractDeconvolution is an important preprocessing procedure often needed in the spectral analysis of transient exponentially decaying signals. Three deconvolution techniques are studied and applied to the problem of estimating the parameters of multiexponential signals observed in noise. Both the conventional and optimal compensated inverse filtering approaches produce data which are further analyzed by SVD-based autoregressive moving average (ARMA) modeling techniques. The third procedure is based on homomorphic filtering and it is implemented by fast Fourier transform (FFT) technique. A comparative study of the performance of the above deconvolution techniques in analyzing multicomponent exponential signals with varied signal-to-noise ratio (SNR) is examined in this paper. The results of simulation studies show that the homomorphic deconvolution technique is most computationally efficient, however, it produces inaccurate estimates of signal parameters even at high SNR, especially with closely related exponents. Simulation results show that the optimal compensation deconvolution technique is indeed a generalized form of the conventional inverse filtering and has the potential of producing accurate estimates of signal parameters from a substantial wide range of SNR data.en_US
dc.identifier.citationSalami, M. J. E., & Sidek, S. N. (2000, September). Performance evaluation of the deconvolution techniques used in analyzing multicomponent transient signals. In 2000 TENCON Proceedings. Intelligent Systems and Technologies for the New Millennium (Cat. No. 00CH37119) (Vol. 1, pp. 487-492). IEEE.en_US
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/498
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectExponentially decaying signalen_US
dc.subjectGardner transformationen_US
dc.subjectOptimal and homomorphic deconvolutionen_US
dc.titlePerformance evaluation of the deconvolution techniques used in analyzing multicomponent transient signalsen_US
dc.typeArticleen_US
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