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Two-Dimensional Fractal Dimension Feature Extraction Algorithm Based On Time-Frequency

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Advanced Hybrid Information Processing (ADHIP 2017)

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Abstract

Digital signal modulation recognition is the technology of signal recognition. In the non-cooperative communication field, the technology is used to process signal and extract feature, and recognize the signal. Because of small distance and intersection between feature classes of digital signal fractal box dimension, its difficult to recognize the signal. This paper proposes a new algorithm. This algorithm is based on time frequency image of two dimensional fractal box dimension feature extraction.

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References

  1. Zhao, Y., Xing, W.: Building a local geomagnetic reference map by the multifractal Kriging based step-by-step interpolation correction method. Appl. Sci. Technol. 06, 1–5 (2015)

    Article  Google Scholar 

  2. Wang, G., Zhang, S., Yan, C., et al.: Probabilistic neural networks and fractal method applied to mineral potential mapping in Luanchuan. In: 2010 Sixth International Conference on Digital Object Identifier, pp. 1003–1007 (2010)

    Google Scholar 

  3. Ivanovici, M., Richard, N.: Fractal dimension of color fractal images. IEEE Trans. Image Process. 20(20), 227–235 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  4. Tang, Z., Yang, X., Li, J.: Study on fractal feature of modulated radio signal. J. Phys. 60(5), 0564701 (2011)

    Google Scholar 

  5. Zhao, C., Ma, S., Yang, W.: Research on spectrum awareness based on fractal box dimension. J. Electron. Inf. Technol. 02, 475–478 (2011)

    Article  Google Scholar 

  6. Chi, F., Hu, Y., Wang, Z.: Feature extraction of turbine blades based on the fractal theory. Appl. Sci. Technol. 04, 64–69 (2015)

    Google Scholar 

  7. Bai, H.: Research on radar emitter signal recognition technology based on time-frequency analysis. People’s Liberation Army Information Engineering University (2012)

    Google Scholar 

  8. Mokni, R., Kherallah, M.: Novel palmprint biometric system combining several fractal methods for texture information extraction. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 002267–002272 (2016)

    Google Scholar 

  9. Zehani, S., Mimi, M., Taleb-Ahmed, A., Toumi, A.: Anisotropy analysis of textures using wavelets transform and fractal dimension. In: 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp. 341–347 (2016)

    Google Scholar 

  10. Jarvenpaa, E., Jarvenpaa, M., Wu, M.: Random affine code tree fractals: hausdorff and affinity dimensions and pressure. In: Mathematical Proceedings of the Cambridge Philosophical Society, vol. 100, pp. 297–300 (2017)

    Google Scholar 

  11. Latorre, E., Layunta, E., Grasa, L.: Intestinal serotonin transporter inhibition by Toll-like receptor 2 activation. A feedback modulation. PLOS One 11(12), e0169303 (2016)

    Article  Google Scholar 

  12. Tam, S.K.E., Hasan, S., Hughes, S.: Modulation of recognition memory performance by light requires both melanopsin and classical photoreceptors. Proc. Roy. Soc. B-Biol. Sci. 283(1845) (2016). https://doi.org/10.6084/m9.figshare.4285250.v1

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Acknowledgments

This paper is funded by the Nation Nature Science Foundation of China (No. 61401115), Nation Nature Science Foundation of China (No. 61301095), Nation Nature Science Foundation of China (No. 61671167). This paper is funded by the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation.

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Authors and Affiliations

  1. Harbin Engineering University, Harbin, 150001, HLJ, China

    Wenwen Li, Zheng Dou & Tingting Cao

Authors
  1. Wenwen Li
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  2. Zheng Dou
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  3. Tingting Cao
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Corresponding author

Correspondence to Wenwen Li .

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Editors and Affiliations

  1. Harbin University of Science and Technology, Harbin, China

    Guanglu Sun

  2. Inner Mongolia University, Hohhot, China

    Shuai Liu

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, W., Dou, Z., Cao, T. (2018). Two-Dimensional Fractal Dimension Feature Extraction Algorithm Based On Time-Frequency. In: Sun, G., Liu, S. (eds) Advanced Hybrid Information Processing. ADHIP 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 219. Springer, Cham. https://doi.org/10.1007/978-3-319-73317-3_18

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  • DOI: https://doi.org/10.1007/978-3-319-73317-3_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73316-6

  • Online ISBN: 978-3-319-73317-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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