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Enhanced Time–Frequency Representation Based on Variational Mode Decomposition and Wigner–Ville Distribution

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Book cover Recent Trends in Image and Signal Processing in Computer Vision

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1124))

Abstract

The Wigner–Ville distribution (WVD) gives a very high-resolution time–frequency distribution but diminishes due to the existence of cross-terms. The cross-terms suppression in WVD is crucial to get the actual energy distribution in time–frequency (TF) plane. This chapter proposes a method to remove both inter and intra cross-terms from TF distribution obtained using WVD. The variational mode decomposition is applied to decompose a multicomponent signal into corresponding mono-components and inter cross-terms are suppressed due to the separation of mono-components. Thereafter, segmentation is applied in time domain to remove intra cross-terms present due to nonlinearity in frequency modulation. The obtained components are processed to get WVD of each component. Finally, all the collected WVDs are added to get complete time–frequency representation. Efficacy of the proposed method is checked using Renyi entropy measure over one synthetic and two natural signals (bat echo sound and speech signal) in clean and noisy environment. The method presented works well and gives better results in comparison to the WVD and pseudo WVD techniques.

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Acknowledgements

The authors wish to thank Curtis Condon, Ken White, and Al Feng of the Beckman Institute of the University of Illinois for the bat data and for permission to use it in this chapter.

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Authors and Affiliations

  1. Department of Electronics Engineering, Defence institute of Advanced Technology, Pune, India

    Rishi Raj Sharma

  2. Discipline of Electrical Engineering, Indian Institute of Technology-Indore, Indore, India

    Preeti Meena & Ram Bilas Pachori

Authors
  1. Rishi Raj Sharma
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  2. Preeti Meena
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  3. Ram Bilas Pachori
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Correspondence to Rishi Raj Sharma .

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Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, Himachal Pradesh, India

    Shruti Jain

  2. Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India

    Sudip Paul

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Sharma, R.R., Meena, P., Pachori, R.B. (2020). Enhanced Time–Frequency Representation Based on Variational Mode Decomposition and Wigner–Ville Distribution. In: Jain, S., Paul, S. (eds) Recent Trends in Image and Signal Processing in Computer Vision. Advances in Intelligent Systems and Computing, vol 1124. Springer, Singapore. https://doi.org/10.1007/978-981-15-2740-1_18

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