A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints

Abstract

Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimization problem with equality and inequality constraints. It is proved that from any initial state, the state… (More)
DOI: 10.1109/TCYB.2016.2567449

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Cite this paper

@article{Qin2017AOR, title={A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints}, author={Sitian Qin and Xiudong Yang and Xiaoping Xue and Jiahui Song}, journal={IEEE Transactions on Cybernetics}, year={2017}, volume={47}, pages={3063-3074} }