Generalization of Hilbert transform for symbolic analysis of noisy signals

Soumik Sarkar, Kushal Mukherjee, Asok Ray

    Research output: Contribution to journalArticle

    20 Citations (Scopus)

    Abstract

    A recent publication has reported a Hilbert-transform-based partitioning method, called analytic signal space partitioning (ASSP), which essentially replaces wavelet space partitioning (WSP) for symbolic analysis of time series data in dynamical systems. When used in conjunction with D-Markov machines, also reported in the recent literature, ASSP provides a fast method of pattern recognition. However, wavelet transform facilitates denoising, which allows D-Markov machines to have a small depth D even if the time series data have a low signal-to-noise ratio. Since Hilbert transform does not specifically address the issue of noise reduction, usage of D-Markov machines with a small D could potentially lead to information loss for noisy signals. On the other hand, a large D tends to make execution of pattern recognition computationally less efficient due to an increased number of machine states. This paper explores generalization of Hilbert transform that addresses symbolic analysis of noise-corrupted dynamical systems. In this context, theoretical results are derived based on the concepts of information theory. These results are validated on time series data, generated from a laboratory apparatus of nonlinear electronic systems.

    Original languageEnglish (US)
    Pages (from-to)1245-1251
    Number of pages7
    JournalSignal Processing
    Volume89
    Issue number6
    DOIs
    StatePublished - Jun 1 2009

    Fingerprint

    Time series
    Pattern recognition
    Dynamical systems
    Information theory
    Noise abatement
    Wavelet transforms
    Signal to noise ratio
    Mathematical transformations

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Software
    • Signal Processing
    • Computer Vision and Pattern Recognition
    • Electrical and Electronic Engineering

    Cite this

    Sarkar, Soumik ; Mukherjee, Kushal ; Ray, Asok. / Generalization of Hilbert transform for symbolic analysis of noisy signals. In: Signal Processing. 2009 ; Vol. 89, No. 6. pp. 1245-1251.
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    Generalization of Hilbert transform for symbolic analysis of noisy signals. / Sarkar, Soumik; Mukherjee, Kushal; Ray, Asok.

    In: Signal Processing, Vol. 89, No. 6, 01.06.2009, p. 1245-1251.

    Research output: Contribution to journalArticle

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