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Performance Comparison of Measurement Matrices in Compressive Sensing

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Advances in Computing and Data Sciences (ICACDS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 905))

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Abstract

Compressive sensing is a new method of signal acquisition and reconstruction through which one can greatly reduce the cost of processing, transmission and storage requirements as compared with the conventional sampling rates. This facilitates the accurate reconstruction of the signals even at sub-Nyquist rates. The role of measurement matrix is indispensable in loyal reconstruction. If the measurement matrix is more obtuse then it takes large computational time for signal reconstruction. This paper mainly focuses on different measurement matrices which are used in compressive sensing. The performance of these measurement matrices for compression and reconstruction of 4 GHz Gaussian modulated sinusoidal pulse are compared in this paper.

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Acknowledgment

This research was supported by Science and Engineering Research Board (SERB), Government of India, under Early Career Research Award scheme (ECR/2016/001563).

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology, Patna, 800005, India

    Kankanala Srinivas, Nagapuri Srinivas, Puli Kishore Kumar & Gayadhar Pradhan

Authors
  1. Kankanala Srinivas
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  2. Nagapuri Srinivas
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  3. Puli Kishore Kumar
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  4. Gayadhar Pradhan
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Corresponding author

Correspondence to Kankanala Srinivas .

Editor information

Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Jaypee University of Information Technology, Solan, India

    P. K. Gupta

  3. Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Institute of Information Theory and Automation, Prague 8, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, Canada

    Tuncer Ören

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Srinivas, K., Srinivas, N., Kumar, P.K., Pradhan, G. (2018). Performance Comparison of Measurement Matrices in Compressive Sensing. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-13-1810-8_34

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  • DOI: https://doi.org/10.1007/978-981-13-1810-8_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1809-2

  • Online ISBN: 978-981-13-1810-8

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