Synapse
⌘+K
Synapse
PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
September 10, 2025An International Journal of Optimization and Control Theories & Applications (IJOCTA)Open Access

Analysis and analytical solution of incommensurate fuzzy fractional nabla difference systems in neural networks

View Full Paper
Ask AI
Bookmark
Share

Authors

BSBabak ShiriEKEhsan Dadkhah KhiabaniDBDumitru Băleanu

Discussion

Loading...

Member takes

Overview

Analysis reveals unique H-differenceable solutions in incommensurate neural networks, highlighting fuzzy theories.

Key Points

  • A unique H-differenceable solution for incommensurate RNNs is established, ensuring fidelity under input uncertainties.
  • The introduction of fuzzy number theory and its operations aids in addressing the complexities of input uncertainties.
  • A recursive algorithm is proposed to derive fuzzy solutions for incommensurate fuzzy fractional nabla difference systems.
  • Illustrative examples validate the framework integrating fuzzy dynamics, fractional calculus, and incommensurate RNNs.

Cite This Study

Shiri et al. (2025) studied this question.

synapsesocial.com/papers/68c1afc054b1d3bfb60e76d8https://doi.org/10.36922/ijocta025130067
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Generalized Incommensurate Fractional Differential Systems: Commensurate and Incommensurate Weight Analyses, Existence-Uniqueness, HU Stability, and Neural Network Applications2026
  2. 2Qualitative and Computational Analysis of Fractional Integro-differential Equations Using Deep Neural Network2026
  3. 3Data Dependence and Existence and Uniqueness for Hilfer Nabla Fractional Difference Equations2024 · 1 citations
  4. 4Numerical and Stability Analysis of Hilfer-Type Fuzzy Fractional Control Systems with Infinite Delay2026 · 1 citations
  5. 5h-Stability of Nonlinear Hilfer Nabla Fractional Difference Equations2026