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

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 constr...

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Veröffentlicht in:	IEEE transactions on cybernetics 2017-10, Vol.47 (10), p.3063-3074
Hauptverfasser:	Qin, Sitian, Yang, Xiudong, Xue, Xiaoping, Song, Jiahui
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computational modeling Convergence Convex functions Global convergence Lyapunov function Neural networks Neural Networks (Computer) Neurodynamics Nonlinear Dynamics Nonlinear programming nonsmooth pseudoconvex optimization one-layer recurrent neural network (RNN) Optimization Recurrent neural networks
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