Mathematical analysis demonstrates conditions for finite-time stability and solution existence in fractional-order neural networks, indicating rapid convergence to equilibrium states.
This article delves into investigating the existence of solutions for fractional-order neural networks (FNN), alongside analyzing the finite-time stability (FTS) of fractional differential equations. FTS, which focuses on trajectories converging to equilibrium within a short time frame, is a central aspect of this exploration. Employing Gronwall's inequality as the primary analytical tool, the study derives conditions for FTS. The theoretical findings are then substantiated through rigorous numerical simulations.
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Kaliraj et al. (2026) studied this question.
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