Recovery of drifting sensor responses by means of DWT analysis

Marzia Zuppa, Cosimo Distante, Krishna C. Persaud, Pietro Siciliano

    Research output: Contribution to journalArticlepeer-review


    This work underlines the ability of the discrete wavelet transform to recover sensor signals subjected to drift effects. The drift resides in low frequencies, so that it is needed to reveal the signal trend. So far, discrete wavelet transform (DWT) is an efficient tool for pre-processing drifting sensor responses as this technique provides a multi-scale processing analysis where the signal is split into low- and high-frequency components at different scales (or different frequency bands) with different resolutions. The trend is the slowest part of the signal and as the scale increases a better estimate of the unknown trend is obtained. Once the signal components, where drift contamination is present, are selected and discarded, the pre-processed signal is not distorted by excessive cutting off low-frequency components. The results are compared with ones obtained by applying standard high-pass filters. © 2006 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)411-416
    Number of pages5
    JournalSensors and Actuators B: Chemical: international journal devoted to research and development of physical and chemical transducers
    Issue number2
    Publication statusPublished - 10 Jan 2007


    • Drift reduction
    • Enose
    • Sammon mapping
    • Wavelet transform


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