Simulating associations and interactions among multiple pieces of brand image using Fuzzy Bidirectional Associative Memory

Author(s):  
Koichi Yamada ◽  
Osamu Onosawa ◽  
Muneyuki Unehara
2021 ◽  
Author(s):  
Yingying Li ◽  
Junrui Li ◽  
Jie Li ◽  
Shukai Duan ◽  
Lidan Wang ◽  
...  

Author(s):  
Y Wang ◽  
P Hu

In this paper, the problem of global robust stability is discussed for uncertain Cohen-Grossberg-type (CG-type) bidirectional associative memory (BAM) neural networks (NNs) with delays. The parameter uncertainties are supposed to be norm bounded. The sufficient conditions for global robust stability are derived by employing a Lyapunov-Krasovskii functional. Based on these, the conditions ensuring global asymptotic stability without parameter uncertainties are established. All conditions are expressed in terms of linear matrix inequalities (LMIs). In addition, two examples are provided to illustrate the effectiveness of the results obtained.


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