Simulation and verification of zhang neural networks and gradient neural networks for time-varying Stein equation solving

Authors:
Chenfu Yi;Yuhuan Chen;Huajin Wang
Affiliations:
School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, China;Center for Educational Technology, Gannan Normal University, Ganzhou, China;School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Year:
2011

Citing 6
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Topics in matrix analysis

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Abstract

Differing from gradient-based neural networks (GNN), In this paper, we present a special kind of recurrent neural networks using a new design method to solve online the time-varying Stein matrix equation A(t)X(t)B(t) + X(t) = C(t). This paper investigates simulation and verification of the resultant Zhang neural networks (ZNN) for the nonstationary Stein equation by using MATLAB simulation techniques. Theoretical analysis and simulation results substantiate the superior performance of the ZNN models for the solution of time-varying Stein equation in real-time, in compared with the GNN models.