Comparative study of adaptive techniques for denoising CN Tower lightning current derivative signals

O. Nedjah, A.M. Hussein, S. Krishnan, R. Sotudeh

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)
    48 Downloads (Pure)

    Abstract

    The lightning current derivative data recorded at the CN Tower during the past 18 years contain different kinds of noise and needs to be denoised for accurately determining the lightning current waveform parameters. It is usually a challenging task to denoise transient signals having large bandwidth without altering their waveshapes or shrinking their amplitudes. This paper deals with denoising the CN Tower lightning current derivative signals using several adaptive techniques. A new adaptive denoising approach (Divide-and-Conquer) has been successfully used to denoise a vast variety of CN Tower lightning current derivative waveshapes. The supremacy of the new technique over the existing ones is outlined for a signal with a poor signal-to-noise ratio (SNR). While keeping the signal amplitude unchanged and preserving its waveshape, the new denoising technique improved its SNR from −22.93 dB to 71.41 dB.
    Original languageEnglish
    Pages (from-to)607-618
    Number of pages12
    JournalDigital Signal Processing
    Volume20
    Issue number2
    DOIs
    Publication statusPublished - 2010

    Keywords

    • CN Tower
    • lightning current derivative
    • adaptive denoising techniques

    Fingerprint

    Dive into the research topics of 'Comparative study of adaptive techniques for denoising CN Tower lightning current derivative signals'. Together they form a unique fingerprint.

    Cite this