Neural Network for Nonsmooth, Nonconvex Constrained Minimization Via Smooth Approximation

@article{Bian2014NeuralNF,
  title={Neural Network for Nonsmooth, Nonconvex Constrained Minimization Via Smooth Approximation},
  author={Wei Bian and Xiaojun Chen},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2014},
  volume={25},
  pages={545-556}
}
A neural network based on smoothing approximation is presented for a class of nonsmooth, nonconvex constrained optimization problems, where the objective function is nonsmooth and nonconvex, the equality constraint functions are linear and the inequality constraint functions are nonsmooth, convex. This approach can find a Clarke stationary point of the optimization problem by following a continuous path defined by a solution of an ordinary differential equation. The global convergence is… CONTINUE READING
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