The bifurcation problems of the four-neuron fractional-order neutral-type inertial neural network (FONTINN) are examined. We study the dynamic characteristics of the system by viewing time delay as the bifurcation parameter. By exploiting the Cramer’s rule, the results with regard to delay-dependent bifurcations are obtained. Experimental results show that when time delay is less than the critical value, the stability of system can be well maintained, and Hopf bifurcation occurs when time delay exceeds its critical value. Furthermore, it also reveals that fractional orders are instrumental in ameliorating the stability of systems in comparison with the traditional integer-order models. The correctness of the discovered theories is ultimately verified through numerical experiments.
- Open Access
- Article
Bifurcations of a Fractional-Order Inertial Neural Network: Neutral-Type Delays
- Chengdai Huang 1,*,
- Huimeng Chen 1,
- Jinde Cao 2,
- Heng Liu 3
Author Information
Received: 23 Apr 2026 | Revised: 05 Jun 2026 | Accepted: 09 Jun 2026 | Published: 20 Jul 2026
Abstract
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