New Results on Interval General Cohen-Grossberg BAM Neural Networks

Aouiti, Chaouki; Dridi, Farah

doi:10.1007/s11424-020-8048-9

Cited by 18 publications

(2 citation statements)

References 48 publications

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“…In addition, in the past few decades, the almost periodic dynamics [26][27][28][29][30][31][32][33] and the almost automorphic dynamics [34][35][36][37][38][39] of deterministic neural networks have been widely studied as one of their important dynamics. And there have been many studies on almost periodic dynamics of stochastic neural networks.…”

Section: Introductionmentioning

confidence: 99%

B‐almost periodic solutions in finite‐dimensional distributions for octonion‐valued stochastic shunting inhibitory cellular neural networks

Huo,

2024

Math Methods in App Sciences

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In this paper, we consider a class of octonion‐valued stochastic shunting inhibitory cellular neural networks with delays. First, we give an estimate of the distance between two different moments of finite‐dimensional distributions of a stochastic process. Then, based on this and by using fixed point theorems and inequality techniques, we establish the existence and global exponential stability of Besicovitch almost periodic ( ‐almost periodic for short) solutions in finite‐dimensional distributions for this kind of networks. Our results are new even if the networks we consider in the paper are real‐valued ones. At the same time, the method proposed in this paper can be applied to study the existence of Besicovitch almost periodic solutions in finite‐dimensional distributions for other types of stochastic neural networks. Finally, an example is given to illustrate the effectiveness of our results.

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Section: Introductionmentioning

confidence: 99%

B‐almost periodic solutions in finite‐dimensional distributions for octonion‐valued stochastic shunting inhibitory cellular neural networks

Huo,

2024

Math Methods in App Sciences

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“…Since 1983 Cohen-Grossberg neural networks are ones of the most investigated neural network models, and numerous qualitative results have been reported in the literature [2]- [6]. The emergence of new results on Cohen-Grossberg type of neural networks demonstrates the importance of research on their dynamic analysis for mathematical, computational, neurophysiological and engineering theories, as well as of their real applications [7], [8].…”

Section: Introductionmentioning

confidence: 99%