Synchronization of BAM Cohen--Grossberg FCNNs with mixed time delays

Document Type : Research Paper


1 Department of Actuarial Science and Applied Statistics, Faculty of Business \& Management, UCSI University, Kuala Lumpur, Malaysia

2 Institute of Computer Science and Digital Innovation, UCSI University, Kuala Lumpur, Malaysia

3 Department of Mathematics, The Gandhigram Rural Institute, Deemed to be University, Gandhigram - 624 302, Dindigul, Tamilnadu, India


This paper deals with the synchronization problem of bidirectional associative memory (BAM) Cohen-Grossberg fuzzy cellular neural networks (CGFCNNs) with discrete time-varying and unbounded distributed delays. Some sufficient conditions are obtained to guarantee the robust synchronization
of BAM CGFCNNs with discrete time-varying and unbounded distributed delays subjected to parametric uncertainty by using Lyapunov-Krasovskii (LK) functional and Linear matrix inequality (LMI) approach.
Sufficient criteria ensure that the error dynamics of considered system is globally asymptotically stable. Finally, numerical examples with simulations are given to show the efficacy of the derived results.