Research on Intelligent Estimation Model of BER for High-Speed Image Transmission Based on LVDS Interface

  • Pengfei LangEmail author
  • Qingfeng Shi
  • Zebing Xie
  • Hongtao Zheng
  • Yan Zhao
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 302)


The high-speed image signal of LVDS interface is easy to be interfered by the outside world in the process of transmission, which results in packet loss and distortion of high-speed image communication, and the output error is high. Therefore, the lossless coding of high-speed image signal is needed. Intelligent estimation of bit error rate (BER) for high-speed image transmission is needed. The intelligent estimation model of high-speed image transmission bit error rate based on LVDS interface is proposed. The network structure model of high-speed image signal transmission is constructed to estimate the error code distortion of image transmission and the key frame feature extraction method is used to estimate the error rate of image transmission. The intelligent estimation of bit error rate (BER) of high-speed image transmission is realized in LVDS interface. The simulation results show that the proposed method has low bit error rate (BER) for high-speed image transmission and achieves lossless transmission of images.


LVDS interface High speed image Transmission Bit error rate Intelligent estimation 


  1. 1.
    Han, D., Chen, X., Lei, Y., et al.: Real-time data analysis system based on Spark Streaming and its application. J. Comput. Appl. 37(5), 1263–1269 (2017)Google Scholar
  2. 2.
    Sun, D.W., Zhang, G.Y., Zheng, W.M.: Big data stream computing, technologies and instances. J. Software 25(4), 839–862 (2014)Google Scholar
  3. 3.
    Hao, S.G., Zhang, L., Muhammad, G.: A union authentication protocol of cross-domain based on bilinear pairing. J. Software 8(5), 1094–1100 (2013)CrossRefGoogle Scholar
  4. 4.
    Hu, S., Ding, Z., Ni, Q.: Beamforming optimisation in energy harvesting cooperative full-duplex networks with self-energy recycling protocol. IET Commun. 10(7), 848–853 (2016)CrossRefGoogle Scholar
  5. 5.
    Seo, D.W., Lee, J.H., Lee, H.S.: Optimal coupling to achieve maximum output power in a WPT system. IEEE Trans. Power Electron. 31(6), 3994–3998 (2016)CrossRefGoogle Scholar
  6. 6.
    Ma, Z., Chen, W.: Friction torque calculation method of ball bearings based on rolling creepage theory. J. Mech. Eng. 53(22), 219–224 (2017)CrossRefGoogle Scholar
  7. 7.
    Zhou, S.B., Xu, W.X.: A novel clustering algorithm based on relative density and decision graph. Control Dec. 33(11), 1921–1930 (2018)zbMATHGoogle Scholar
  8. 8.
    He, H., Tan, Y.: Automatic pattern recognition of ECG signals using entropy-based adaptive dimensionality reduction and clustering. Appl. Soft Comput. 55, 238–252 (2017)CrossRefGoogle Scholar
  9. 9.
    Zhu, Y., Zhu, X., Wang, J.: Time series motif discovery algorithm based on subsequence full join and maximum clique. J. Comput. Appl. 39(2), 414–420 (2019)Google Scholar
  10. 10.
    Dai, H., Huang, Y., Li, C., et al.: Energy-efficient resource allocation for device-to-device communication with WPT. IET Commun. 11(3), 326–334 (2017)CrossRefGoogle Scholar
  11. 11.
    Helmy, A., Hedayat, A., Al-Dhahir, N.: Robust weighted sum-rate maximization for the multi-stream MIMO interference channel with sparse equalization. IEEE Trans. Commun. 60(10), 3645–3659 (2015)CrossRefGoogle Scholar
  12. 12.
    Alfaro, V.M., Vilanoab, R.: Robust tuning of 2DoF five-parameter PID controllers for inverse response controlled processes. J. Process Control 23(4), 453–462 (2013)CrossRefGoogle Scholar
  13. 13.
    Zhang, R., Zhao, F.: Foggy image enhancement algorithm based on bidirectional diffusion and shock filtering. Comput. Eng. 44(10), 221–227 (2018)Google Scholar
  14. 14.
    Liu, D., Zhou, D., Nie, R., Hou, R.: Multi-focus image fusion based on phase congruency motivate pulse coupled neural network-based in NSCT domain. J. Comput. Appl. 38(10), 3006–3012 (2018)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Pengfei Lang
    • 1
    Email author
  • Qingfeng Shi
    • 1
  • Zebing Xie
    • 1
  • Hongtao Zheng
    • 1
  • Yan Zhao
    • 2
  1. 1.China Academy of Launch Vehicle TechnologyBeijingChina
  2. 2.School of Power EngineeringNanjing Institute of TechnologyNanjingChina

Personalised recommendations