Stability analysis of fractional-order quaternion-valued neural networks with multiple delays and parameter uncertainties Article Swipe

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Guoqing Jiang , Xiaolan Liu , Lei Wang , Chongwei Zheng ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.3934/math.2025553

This paper proposes a fractional-order quaternion-valued neural network (FOQVNN) model with dual proportional delays, neutral delays, and parameter uncertainties. By leveraging classical lemmas and a relaxed linear matrix inequality (LMI) condition, we prove not only the uniqueness of the equilibrium point in the proposed model, but also the global robust stability of this equilibrium. Finally, numerical simulations were provided to validate the theoretical results.

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Quaternion Stability (learning theory) Mathematics Artificial neural network Applied mathematics Order (exchange) Control theory (sociology) Computer science Artificial intelligence Machine learning Economics Geometry Control (management) Finance

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Type: article
Language: en
Landing Page: https://doi.org/10.3934/math.2025553
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References: 41
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Title: Stability analysis of fractional-order quaternion-valued neural networks with multiple delays and parameter uncertainties

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Publication year: 2025

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Authors: Guoqing Jiang, Xiaolan Liu, Lei Wang, Chongwei Zheng

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Landing page: https://doi.org/10.3934/math.2025553

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Concepts: Quaternion, Stability (learning theory), Mathematics, Artificial neural network, Applied mathematics, Order (exchange), Control theory (sociology), Computer science, Artificial intelligence, Machine learning, Economics, Geometry, Control (management), Finance

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