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A fully complex-valued neural network for rapid solution of complex-valued systems of linear equations

  • Lin Xiao
  • , Weiwei Meng
  • , Rongbo Lu
  • , Xi Yang
  • , Bolin Liao
  • , Lei Ding
  • Jishou University
  • Delaware State University

科研成果: 期刊稿件会议文章同行评审

摘要

In this paper, online solution of complex-valued systems of linear equations is investigated in the complex domain. Different from the conventional real-valued neural network, which is only designed for realvalued linear equations solving, a fully complex-valued gradient neural network (GNN) is developed for online complex-valued systems of linear equations. The advantages of the proposed complex-valued GNN model decrease the unnecessary complexities in theoretical analysis, real-time computation and related applications. In addition, the theoretical analysis of the fully complex-valued GNN model is presented. Finally, simulative results substantiate the effectiveness of the fully complex-valued GNN model for online solution of the complex-valued systems of linear equations in the complex domain.

源语言英语
页(从-至)444-451
页数8
期刊Lecture Notes in Computer Science
9377 LNCS
DOI
出版状态已出版 - 2015
已对外发布
活动12th International Symposium on Neural Networks, ISNN 2015 - Jeju, 韩国
期限: 15 10月 201518 10月 2015

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