Improved system blind identification based on second-order cyclostationary statistics: A group delay approach | Zendy

P V. S. Giridhar | Zendy; S.V. Narasimhan | Zendy

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Improved system blind identification based on second-order cyclostationary statistics: A group delay approach

Author(s) -

P V. S. Giridhar,

S.V. Narasimhan

Publication year - 2000

Publication title -

sadhana

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.268

H-Index - 49

eISSN - 0973-7677

pISSN - 0256-2499

DOI - 10.1007/bf02703751

Subject(s) - cyclostationary process , statistics , higher order statistics , group delay and phase delay , mathematics , mean squared error , identification (biology) , system identification , noise (video) , algorithm , root mean square , signal processing , speech recognition , computer science , telecommunications , artificial intelligence , engineering , data mining , channel (broadcasting) , radar , botany , bandwidth (computing) , electrical engineering , image (mathematics) , biology , measure (data warehouse)

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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