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Application of Non-uniform Sampling in Compressed Sensing for Speech Signal

  • Changqing Zhang
  • Gang Min
  • Huan Ma
  • Xian Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

Currently, the most widely used Gaussian random observations in compressed sensing require that signals must be discrete, and the signal waveform must be known before observation, which greatly restricts the application of compressive sensing in speech. In response to this problem, this paper draws on the advantages of non-uniform sampling, constructs a non-uniform observation matrix, directly extracts the data from the signal waveform as observations, and gives a corresponding new method of reconstruction. The theoretical analysis and simulation results show that non-uniform observation can directly apply compressed sensing to analog speech signal processing, and the corresponding reconstruction method effectively enriches the means of compressive perception reconstruction.

Keywords

Compressed sensing Non-uniform sampling Speech signal 

References

  1. 1.
    Guangming, S., Danhua, L., Dahua, G., et al.: Advances in theory and application of compressed sensing. Acta Electronica Sin. 37(5), 1070–1081 (2009)Google Scholar
  2. 2.
    Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Lu, X.: Research on MIMO Radar Imaging for Sparse Distributed Target. University of Science and Technology of China, pp. 87–88 (2017)Google Scholar
  4. 4.
    Jinchao, L., Zhaoxiang, D., Yanjun, J., et al.: Spectrum analysis and weak signal detection based on nonuniform sampling. J. Data Acquis. Process. 27(3), 320–326 (2012)Google Scholar
  5. 5.
    Qian Hui, Yu., Lun, Z.H.: Performance analysis of parameters sparse signal nonuniform sampling. Comput. Digit. Eng. 39(7), 24–26 (2011)Google Scholar
  6. 6.
    Kai, Yu., Yuanshi, L., Zhi, W., et al.: New method for acoustic signal collection based on compressed sampling. Chin. J. Sci. Instrum. 33(1), 105–112 (2012)Google Scholar
  7. 7.
    Wenbiao, T., Guosheng, R., Haibo, Z., et al.: Non-uniform information acquisition and reconstruction within compressed sensing framework. J. Jilin Univ. (Eng. Technol. Edn.) 44(4), 1209–1214 (2014)Google Scholar
  8. 8.
    Dongliang, G., Tiejun, Z., Xianhua, D.: Methods of signal frequency, amplitude and phase measurement based on non-uniform sampling. Syst. Eng. Electron. 34(4), 662–665 (2012)Google Scholar
  9. 9.
    Qing, L.: The Research of Compressed Sampling at Sensor Network Nodes. Tianjin University of Technology, pp. 15–17 (2014)Google Scholar
  10. 10.
    Zhou, J., Shi, Z., Hu, L., et al.: Radar target one dimensional high resolution imaging based on sparse and non-uniform samplings in frequency domain. Acta Electronica Sin. 40(5), 926–934 (2012)Google Scholar
  11. 11.
    Anming, W., Shu, W., Mingxin, C.: Study on spectrum of nonuniform sampling signals based on wavelet transform. J. Electron. Inf. Technol. 27(3), 427–430 (2005)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Information and CommunicationNational University of Defense TechnologyXi’anChina

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