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A Neural Network for Constrained Saddle Point Problems: An Approximation Approach

  • Xisheng Shen
  • Shiji Song
  • Lixin Cheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3610)

Abstract

This paper proposes a neural network for saddle point problems (SPP) by an approximation approach. It first proves both the existence and the convergence property of approximate solutions, and then shows that the proposed network is globally exponentially stable and the solution of (SPP) is approximated. Simulation results are given to demonstrate further the effectiveness of the proposed network.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xisheng Shen
    • 1
    • 2
  • Shiji Song
    • 1
  • Lixin Cheng
    • 2
  1. 1.Department of AutomationTsinghua UniversityBeijingChina
  2. 2.School of Mathematical SciencesXiamen UniversityFujianChina

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