An improved system blind identification method based on second-order cyclostationary statistics and the properties of group delay, has been proposed. This is achieved by applying a correction to the estimated phase (by the spectral correlation density of the system output) for the poles, in the group delay domain. The results indicate a significant improvement in system blind identification, in terms of root mean square error. Depending upon the signal-to-noise ratio, the improvement in percentage normalized mean square error ranges between 20 and 50%.

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dc.contributor.authorGiridhar, P.V.S.
dc.contributor.authorNarasimhan, S.V.
dc.date.accessioned2026-02-05T11:00:32Z
dc.date.issuedImproved system blind identification based on second-order cyclostationary statistics: A group delay approach
dc.description.abstract2000
dc.identifier.citationSadhana - Academy Proceedings in Engineering Sciences, 2000, 25, 2, pp. 85-96
dc.identifier.issn2562499
dc.identifier.urihttps://doi.org/10.1007/BF02703751
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/28026
dc.subjectDecision support systems
dc.subjectFunctions
dc.subjectSignal to noise ratio
dc.subjectSpectrum analysis
dc.subjectStatistical methods
dc.subjectSystem theory
dc.subjectBlind identification
dc.subjectGroup delay approach
dc.subjectSecond order cyclostationary statistics
dc.subjectIdentification (control systems)
dc.titleAn improved system blind identification method based on second-order cyclostationary statistics and the properties of group delay, has been proposed. This is achieved by applying a correction to the estimated phase (by the spectral correlation density of the system output) for the poles, in the group delay domain. The results indicate a significant improvement in system blind identification, in terms of root mean square error. Depending upon the signal-to-noise ratio, the improvement in percentage normalized mean square error ranges between 20 and 50%.

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