Differential Inclusions-Based Neural Networks for Nonsmooth Convex Optimization on a Closed Convex Subset

  • Shiji Song
  • Guocheng Li
  • Xiaohong Guan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


Differential inclusions-based dynamic feedback neural network models are introduced to solve in real time nonsmooth convex optimization problems restricted on a closed convex subset of R n . First,a differential inclusion-based dynamic feedback neural network model for solving unconstrained optimization problem is established, and its stability and convergence are investigated, then based on the preceding results and the method of successive approximation, differential inclusions-based dynamic feedback neural network models for solving in real time nonsmooth optimization problem on a closed convex subset are successively constructed, and its dynamical behavior and optimization capabilities are analyzed rigorously.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shiji Song
    • 1
  • Guocheng Li
    • 1
  • Xiaohong Guan
    • 1
  1. 1.Department of AutomationTsinghua UniversityBeijingChina

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