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Random periodic oscillations and global mean-square exponential stability of discrete-space and discrete-time stochastic competitive neural networks with Dirichlet boundary condition.
- Source :
-
Journal of Intelligent & Fuzzy Systems . 2023, Vol. 45 Issue 3, p3729-3748. 20p. - Publication Year :
- 2023
-
Abstract
- The current article explores the affects of space-time discrete stochastic competitive neural networks. In line with a discrete-space and discrete-time constant variation formula, boundedness and stability are addressed to the space-time discrete stochastic competitive neural networks. Notably, the best convergence speed can be computed by a non-linear optimization problem. In the end, random periodic sequences with respect to time variable of the discrete-space and discrete-time stochastic competitive neural networks are discussed. The results indicate that spatial diffusion with non-negative density factors has no effect on the global mean square boundedness and stability and random periodicity of the network model. The current article is precursory in consideration of space-time discrete competitive neural networks. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 45
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 172806268
- Full Text :
- https://doi.org/10.3233/JIFS-230821