Affiliations: [a] Department of Mathematics, School of Advanced Sciences, Kalasalingam Academy of Research and Education, Krishnankoil, India
| [b] Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
| [c] Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, PR China
Correspondence:
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Corresponding author. Changjin Xu, Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, PR China. E-mail: [email protected].
Abstract: This research investigates the presence of unique solutions and quasi-uniform stability for a class of fractional-order uncertain BAM neural networks utilizing the Banach fixed point concept, the contraction mapping principle, and analysis techniques. In order to guarantee the equilibrium point of fractional-order BAM neural networks with undetermined parameters, some new adequate criteria are devised, and both time delays result in quasi-uniform stability. The acquired results, which are simple to verify in practice, enhance and extend several earlier research works in some ways. Finally, two illustrative examples are provided to show the value of the suggested outcomes.
