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Mean-square exponential input-to-state stability for stochastic neutral-type quaternion-valued neural networks via Itô’s formula of quaternion version

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  • Zeng, Runtian
  • Song, Qiankun

Abstract

The input-to-state stability of stochastic quaternion-valued neural networks with neutral delays is explored in this study. Unlike previous researches, this study treats the neural network as a unified entity, rather than isolating and examining the real and imaginary components separately. Through the construction of a Lyapunov functional and the use of the Itô’s formula of quaternion version, a sufficient criterion for achieving mean-square exponential input-to-state stability is obtained for stochastic quaternion-valued neural networks with neutral delays. Three numerical instances are presented to validate the reliability of the obtained conditions.

Suggested Citation

  • Zeng, Runtian & Song, Qiankun, 2024. "Mean-square exponential input-to-state stability for stochastic neutral-type quaternion-valued neural networks via Itô’s formula of quaternion version," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012432
    DOI: 10.1016/j.chaos.2023.114341
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    References listed on IDEAS

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    1. Tong Wang & Yongsheng Ding & Lei Zhang & Kuangrong Hao, 2015. "Delay-dependent exponential state estimators for stochastic neural networks of neutral type with both discrete and distributed delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(4), pages 670-680, March.
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    4. Usa Humphries & Grienggrai Rajchakit & Pramet Kaewmesri & Pharunyou Chanthorn & Ramalingam Sriraman & Rajendran Samidurai & Chee Peng Lim, 2020. "Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
    5. Kwon, Yongchan & Won, Joong-Ho & Kim, Beom Joon & Paik, Myunghee Cho, 2020. "Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation," Computational Statistics & Data Analysis, Elsevier, vol. 142(C).
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