Zhang Neural Network Versus Gradient Neural Network for Online Time-Varying Quadratic Function Minimization

Authors:
Yunong Zhang;Zhan Li;Chenfu Yi;Ke Chen
Affiliations:
School of Information Science and Technology, ,;School of Information Science and Technology, ,;School of Information Science and Technology, ,;School of Software, Sun Yat-Sen University, Guangzhou, China 510275
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

With the proved efficacy on solving linear time-varying matrix or vector equations, Zhang neural network (ZNN) could be generalized and developed for the online minimization of time-varying quadratic functions. The minimum of a time-varying quadratic function can be reached exactly and rapidly by using Zhang neural network, as compared with conventional gradient-based neural networks (GNN). Computer-simulation results substantiate further that ZNN models are superior to GNN models in the context of online time-varying quadratic function minimization.