Cramer-rao lower bound for parameter estimation of multiexponential signals

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dc.contributor.authorJibia, Abdussamad U.
dc.contributor.authorSalami, Momoh-Jimoh E.
dc.contributor.authorKhalifa, Othman O.
dc.contributor.authorElfaki, Faiz A. M.
dc.date.accessioned2019-10-24T13:42:54Z
dc.date.available2019-10-24T13:42:54Z
dc.date.issued2009-05-18
dc.description.abstractThe Cramer Rao Lower Bound on the mean square error of unbiased estimators is widely used as a measure of accuracy of parameter estimates obtained from a given data. In this paper, derivation of the Cramer-Rao Bound on real decay rates of multiexponential signals buried in white Gaussian noise is presented. It is then used to compare the efficiencies of some of the techniques used in the analysis of such signals. Specifically, two eigendecomposition-based techniques as well as SVD-ARMA (Singular Value Decomposition Autoregressive Moving Average) method are tested and evaluated. The two eigenvector methods were found to outperform SVD-ARMA with minimum norm being the most reliable at very low SNRs (Signal to Noise Ratios).en_US
dc.identifier.citationJibia, A. U., Salami, M. J. E., Khalifa, O. O., & Elfaki, F. A. (2009, June). Cramer-rao lower bound for parameter estimation of multiexponential signals. In 2009 16th International Conference on Systems, Signals and Image Processing (pp. 1-5). IEEE.en_US
dc.identifier.uri10.1109/IWSSIP.2009.5367779
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/605
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectParameter estimationen_US
dc.subjectTestingen_US
dc.subjectIntegral equationsen_US
dc.subjectMean square error methodsen_US
dc.subjectGaussian noiseen_US
dc.subjectConvolutionen_US
dc.subjectDeconvolutionen_US
dc.subjectNoise generatorsen_US
dc.subjectTransient analysisen_US
dc.subjectData engineeringen_US
dc.titleCramer-rao lower bound for parameter estimation of multiexponential signalsen_US
dc.typeArticleen_US
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