Citation: | Xueying Shi, Xiaoping Chen, Chengdai Huang. DELAY-INDUCED HOPF BIFURCATION OF A FRACTIONAL-ORDER NEURAL NETWORK WITH BOTH NEUTRAL AND INERTIAL TERMS[J]. Journal of Applied Analysis & Computation, 2026, 16(1): 362-379. doi: 10.11948/20250068 |
This paper focuses on the stability and bifurcation in a fractional-order neutral-type inertial neural network with time delay. We mainly analyze the new system with time delay by using Cramer's rule to derive precise bifurcation conditions. The accuracy of the theoretical findings is ultimately confirmed through two numerical experiments. Moreover, the remarkable advantages of the fractional-order model are found in delaying the occurrence of inherent bifurcations and enhancing the stability performance.
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The waveform diagrams of system (5.1) with
The phase diagrams of system (5.1) with
The waveform diagrams of system (5.1) with
The phase diagrams of system (5.1) with
Influence of
Comparison on the stability of system (5.1) in integer-order and fractional-order.
Comparison on the stability of system (5.1) in integer-order and fractional-order.
Comparison on the stability of system (5.1) in integer-order and fractional-order.
Comparison on the stability of system (5.1) in integer-order and fractional-order.
The waveform diagrams of system (5.2) with
The phase diagrams of system (5.2) with
The waveform diagrams of system (5.2) with
The phase diagrams of system (5.2) with
Influence of
Comparison on the stability of system (5.2) in integer-order and fractional-order.
Comparison on the stability of system (5.2) in integer-order and fractional-order.
Comparison on the stability of system (5.2) in integer-order and fractional-order.
Comparison on the stability of system (5.2) in integer-order and fractional-order.