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A simple improvement to Tufts-Kumaresan method for multiple sinusoidal frequency estimation

Hing-Cheung So, Chi-Tim Leung

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Tufts-Kumaresan (TK) method, which is based on linear prediction approach, is a standard algorithm for estimating the frequencies of sinusoids in noise. In this Letter, the TK algorithm is improved by attenuating the noise in the observation vector with the use of the reduced rank data matrix. It is shown that the proposed modification can provide smaller mean square frequency errors with lower threshold signal-to-noise ratios than the TK method and a total least squares solution. Copyright © 2005 The Institute of Electronics, Information and Communication Engineers.
    Original languageEnglish
    Pages (from-to)381-383
    JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
    VolumeE88-A
    Issue number1
    DOIs
    Publication statusPublished - Jan 2005

    Research Keywords

    • Frequency estimation
    • Multiple sinusoids

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