LMI criteria on exponential stability of BAM neural networks with both time-varying delays and general activation functions

Huiwei Wang, Qiankun Song and Chengjun Duan

Mathematics and Computers in Simulation (MATCOM), 2010, vol. 81, issue 4, 837-850

Abstract: In this paper, the exponential stability analysis for the bidirectional associative memory neural network model with both time-varying delays and general activation functions is considered. Neither the boundedness and the monotony on these activation functions nor the differentiability on the time-varying delays are assumed. By employing Lyapunov functional and the linear matrix inequality (LMI) approach, several new sufficient conditions in LMI form are obtained to ensure the existence, uniqueness and global exponential stability of equilibrium point for the neural networks. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The proposed stability results are less conservative than some recently known ones in the literature, which is demonstrated via an example with simulation.

Keywords: BAM neural networks; Time-varying delays; Exponential stability; Linear matrix inequality (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:81:y:2010:i:4:p:837-850

DOI: 10.1016/j.matcom.2010.08.011

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