A general methodology for designing globally convergent optimization neural networks

@article{Xia1998AGM,
  title={A general methodology for designing globally convergent optimization neural networks},
  author={Youshen Xia and Jun Wang},
  journal={IEEE transactions on neural networks},
  year={1998},
  volume={9 6},
  pages={1331-43}
}
In this paper, we present a general methodology for designing optimization neural networks. We prove that the neural networks constructed by using the proposed method are guaranteed to be globally convergent to solutions of problems with bounded or unbounded solution sets, in contrast with the gradient methods whose convergence is not guaranteed. We show that the proposed method contains both the gradient methods and nongradient methods employed in existing optimization neural networks as… CONTINUE READING
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