Multi-label algorithm based on rough set of fractal dimension attribute

  • Zhibin ZhangEmail author
  • Deyu Li


To make fractal endpoint detection algorithm, to maintain good performance and to deal with noise with higher irregularity than speech, fractal endpoint detection algorithm based on frequency domain was proposed in the paper. The frequency domain represented energy distribution and signal, and the speech harmonic component had very strong periodicity and regularity in the frequency domain. Thus, method of extracting fractal dimension after converting to short-time frequency domain had better robustness. Analysis means were introduced based on short-time frequency domain fractal against the existing fractal algorithm. Its stability was due to the frequency domain represented frequency domain energy distribution of signal and the speech signal energy mainly focused on harmonic. Thus, solving fractal dimension in short-time frequency domain could weaken the impact of different types of noises. Compared with time-domain fractal, the threshold value of short-time frequency domain fractal was more stable and the judgment criterion direction was fixed, smaller than the represented speech fragment of threshold value. Frequency domain was used for representing the signal energy distribution characteristics and the strong periodicity and regularity of speech harmonic component so as to extract fractal dimension and distinguish speech and noise. Thus, the fractal dimension extraction method after converting to short-time frequency domain proposed in the paper had better robustness. Not only is it applicable to irregular white noise, but also applicable to noises with stronger time-domain periodicity and regularity including tank noise.


Fractal algorithm Rough set Label Short-time frequency domain Harmonic component 


  1. 1.
    Lange RSAD, Hekkink JHA, Keizer K et al (2017) Formation and characterization of supported microporous ceramic membranes prepared by sol–gel modification techniques. J Membr Sci 99(1):57–75CrossRefGoogle Scholar
  2. 2.
    Harker DE, Wooden DH, Woodward CE et al (2015) Grain properties of comet C/1995 O1 (Hale-Bopp). Astrophys J 580(1):579CrossRefGoogle Scholar
  3. 3.
    Miranda SM, Romanos GE, Likodimos V et al (2014) Pore structure, interface properties and photocatalytic efficiency of hydration/dehydration derived TiO2/CNT composites. Appl Catal B Environ 147(147):65–81CrossRefGoogle Scholar
  4. 4.
    Neogi N, Mohanta DK, Dutta PK (2014) Review of vision-based steel surface inspection systems. Eurasip J Image Video Process 2014(1):50CrossRefGoogle Scholar
  5. 5.
    Stateczny A, Wlodarczyk-Sielicka M (2014) Self-organizing artificial neural networks into hydrographic big data reduction process. In: International Conference on Rough Sets and Intelligent Systems Paradigms. Springer, Cham, pp 335–342Google Scholar
  6. 6.
    Ge Y, Kulatilake PHSW, Tang H et al (2014) Investigation of natural rock joint roughness. Comput Geotech 55(55):290–305CrossRefGoogle Scholar
  7. 7.
    Tarquis AM, Platonov A, Matulka A et al (2014) Application of multifractal analysis to the study of SAR features and oil spills on the ocean surface. Nonlinear Process Geophys 21(2):439–450CrossRefGoogle Scholar
  8. 8.
    Ciavarella M (2015) Adhesive rough contacts near complete contact. Int J Mech Sci 104:104–111CrossRefGoogle Scholar
  9. 9.
    Ai T, Zhang R, Zhou HW et al (2014) Box-counting methods to directly estimate the fractal dimension of a rock surface. Appl Surf Sci 314(10):610–621CrossRefGoogle Scholar
  10. 10.
    Peng G, Xiang N, Lv SQ et al (2014) Fractal characterization of soil particle-size distribution under different land-use patterns in the Yellow River Delta Wetland in China. J Soils Sediments 14(6):1116–1122CrossRefGoogle Scholar
  11. 11.
    Liu Y, Wang Y, Chen X et al (2017) Two-stage method for fractal dimension calculation of the mechanical equipment rough surface profile based on fractal theory. Chaos Solitons Fractals 104(4):495–502CrossRefGoogle Scholar
  12. 12.
    Mance B (2014) Number theoretic applications of a class of Cantor series fractal functions. I. Int J Number Theory 144(2):449–493MathSciNetzbMATHGoogle Scholar
  13. 13.
    Mohammed MA, Ghani MKA, Arunkumar N, Hamed RI, Mostafa SA, Abdullah MK, Burhanuddin MA (2018) Decision support system for nasopharyngeal carcinoma discrimination from endoscopic images using artificial neural network. J Supercomput. Google Scholar
  14. 14.
    Mohammed MA, Ghani MKA, Arunkumar N, Hamed RI, Abdullah MK, Burhanuddin MA (2018) A real time computer aided object detection of nasopharyngeal carcinoma using genetic algorithm and artificial neural network based on Haar feature fear. Future Gener Comput Syst. Google Scholar
  15. 15.
    Al-Bashir A, Al-Abed M, Amari H, Al-Rousan F, Bashmaf O, Abdulhay E, Al Abdi R, ArunKumar N, Tapas Bapu BR, Al-Basheer A (2015) Computer-based cobb angle measurement using deflection points in adolescence idiopathic scoliosis from radiographic images. Neural Comput Appl. Google Scholar
  16. 16.
    Khanna A, Jain S, Aggarwal T, kumar A, Gupta D, Julka A, Albuquerque V (2018) Optimized cuttlefish algorithm for diagnosis of parkinson’s disease. Cognit Syst Res 52:36–48CrossRefGoogle Scholar
  17. 17.
    Hussein AF, ArunKumar N, Ramirez-Gonzalez G, Abdulhay E, Tavares JMR, de Albuquerque VHC (2018) A medical records managing and securing blockchain based system supported by a genetic algorithm and discrete wavelet transform. Cognit Syst Res 52:1–11. CrossRefGoogle Scholar
  18. 18.
    Wei J, Meng F, Arunkumar N (2018) A personalized authoritative user-based recommendation for social tagging. Future Gener Comput Syst. Google Scholar
  19. 19.
    Ashokkumar P, Arunkumar N, Don S (2018) Intelligent optimal route recommendation among heterogeneous objects with keywords. Comput Electr Eng 68:526–535CrossRefGoogle Scholar
  20. 20.
    Hussein AF, Kumar A, Burbano-Fernandez M, Ramirez-Gonzalez G, Abdulhay E, de Albuquerque VHC (2018) An automated remote cloud-based heart rate variability monitoring system. IEEE Access. Google Scholar
  21. 21.
    Sarvaghad-Moghaddam M, Orouji AA, Ramezani Z, Elhoseny M, Farouk A, Arun kumar N (2018) Modelling the spice parameters of SOI MOSFET using a combinational algorithm. Cluster Comput. Google Scholar
  22. 22.
    Elhoseny M, Ramírez-González G, Abu-Elnasr OM, Shawkat SA, Arunkumar N, Farouk A (2018) Secure medical data transmission model for IoT-based healthcare systems. IEEE Access. Google Scholar
  23. 23.
    Vardhana M, Arunkumar N, Abdulhay E, Ramirez-Gonzalez G (2018) Convolutional neural network for bio-medical image segmentation with hardware acceleration. Cognit Syst Res 50:10–14CrossRefGoogle Scholar
  24. 24.
    Tharwat A, Elhoseny M, Hassanien AE, Gabel T, Arunkumar N (2018) Intelligent Bézier curve-based path planning model using chaotic particle swarm optimization algorithm. Cluster Comput. Google Scholar
  25. 25.
    Arunkumar N, Ramkumar K, Venkatraman V (2018) Entropy features for focal EEG and non focal EEG. J Comput Sci. MathSciNetGoogle Scholar
  26. 26.
    Liu C, Arunkumar N (2018) Risk prediction and evaluation of transnational transmission of financial crisis based on complex network. Cluster Comput. Google Scholar
  27. 27.
    Meng G, Arunkumar N (2018) Construction of employee training program evaluation system of three exponential forecast based on sliding window. Cluster Comput. Google Scholar
  28. 28.
    Chen X, Pang L, Guo P, Sun X, Xue Z, Arunkumar N (2017) New upper degree of freedom in transmission system based on wireless G-MIMO communication channel. Cluster Comput. Google Scholar
  29. 29.
    Hamza R, Muhammad K, Arunkumar N, Ramírez González G (2017) Hash based encryption for keyframes of diagnostic hysteroscopy. IEEE Access. Google Scholar
  30. 30.
    Fernandes SL, Gurupur VP, Sunder NR, Arunkumar N, Kadry S (2017) A novel nonintrusive decision support approach for heart rate measurement. Pattern Recognit Lett. Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer and Information TechnologyShanxi UniversityTaiyuanChina

Personalised recommendations