• Infrared and Laser Engineering
  • Vol. 44, Issue 2, 715 (2015)
Ruan Xiukai1、2、*, Tang Zhenzhou1, Zhang Yaoju1、2, Chen Xiaojing1, and Chen Huiling1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    DOI: Cite this Article
    Ruan Xiukai, Tang Zhenzhou, Zhang Yaoju, Chen Xiaojing, Chen Huiling. Electrical blind detection of coherent optical communication signals using feedback-voltage-bias-type Hopfield neural network[J]. Infrared and Laser Engineering, 2015, 44(2): 715 Copy Citation Text show less

    Abstract

    To solve the special issue of electrical adaptive blind equalization in wireless spatial diversity optical coherent receivers, a new blind detection algorithm of multi-value QAM signals using output-feedback-bias(OFB) type complex discrete-time continuous state(DTCS) Hopfield neural network was presented. The OFB will not change the traditional Hopfield model. The proposed OFB-DTCS Hopfield neural network can meet special requirement of the multi-valued signal detection which need enlarger the search space. The blind detection problem of multi-valued QAM signals was transformed into solving a quadratic optimization problem. How to map the cost function of this optimization problem to the energy function of OFB-DTCS Hopfield neural network was also shown. The proof, analysis and its constraints of the energy function were shown, respectively. A complex activation function to fit this special problem was discussed. Then a special connective matrix was constructed to ensure algorithm detect signals correctly. Finally, detailed simulation results and performance comparison with other algorithm were shown to demonstrate farther the effectiveness, superiority and shortage of this new algorithm.
    Ruan Xiukai, Tang Zhenzhou, Zhang Yaoju, Chen Xiaojing, Chen Huiling. Electrical blind detection of coherent optical communication signals using feedback-voltage-bias-type Hopfield neural network[J]. Infrared and Laser Engineering, 2015, 44(2): 715
    Download Citation