Multistability of delayed fractional-order competitive neural networks.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 33895556.
- Also identified by DOI 10.1016/j.neunet.2021.03.036.
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Abstract
This paper is concerned with the multistability of fractional-order competitive neural networks (FCNNs) with time-varying delays. Based on the division of state space, the equilibrium points (EPs) of FCNNs are given. Several sufficient conditions and criteria are proposed to ascertain the multiple O(t<sup>-α</sup>)-stability of delayed FCNNs. The O(t<sup>-α</sup>)-stability is the extension of Mittag-Leffler stability of fractional-order neural networks, which contains monostability and multistability. Moreover, the attraction basins of the stable EPs of FCNNs are estimated, which shows the attraction basins of the stable EPs can be larger than the divided subsets. These conditions and criteria supplement and improve the previous results. Finally, the results are illustrated by the simulation examples.
Medical subject headings
- Neural Networks, Computer