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Finds conditions ensuring stability of anti-periodic solutions in fuzzy neural networks, suggesting improvements in computational models.
This study investigates fuzzy shunting inhibitory cellular neural networks (FSICNNs) with time-varying parameters and delays. We focus on a specialised class of solutions known as pseudo S-asymptotically ω-anti-periodic solutions. Using the Banach fixed point theorem and fuzzy set theory, we establish rigorous existence and uniqueness theorems for these solutions. Furthermore, we derive sufficient conditions that ensure their global exponential stability. The theoretical results are validated through numerical simulations.
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Aouiti et al. (2026) studied this question.
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