Fanghai Zhang

Orcid: 0000-0002-6022-7499

Affiliations:
  • Huazhong University of Science and Technology, Wuhan, Hubei, China


According to our database1, Fanghai Zhang authored at least 14 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Mittag-Leffler stability and application of delayed fractional-order competitive neural networks.
Neural Networks, 2024

2022
Multistability and Stabilization of Fractional-Order Competitive Neural Networks With Unbounded Time-Varying Delays.
IEEE Trans. Neural Networks Learn. Syst., 2022

2021
Asymptotic Stability and Synchronization of Fractional-Order Neural Networks With Unbounded Time-Varying Delays.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Multiple ψ-Type Stability of Cohen-Grossberg Neural Networks With Unbounded Time-Varying Delays.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Multistability of Fractional-Order Neural Networks With Unbounded Time-Varying Delays.
IEEE Trans. Neural Networks Learn. Syst., 2021

Multiple Mittag-Leffler Stability of Delayed Fractional-Order Cohen-Grossberg Neural Networks via Mixed Monotone Operator Pair.
IEEE Trans. Cybern., 2021

Robust Stability of Recurrent Neural Networks With Time-Varying Delays and Input Perturbation.
IEEE Trans. Cybern., 2021

Multistability of delayed fractional-order competitive neural networks.
Neural Networks, 2021

Multistability and robustness of complex-valued neural networks with delays and input perturbation.
Neurocomputing, 2021

2020
Multiple Lagrange Stability Under Perturbation for Recurrent Neural Networks With Time-Varying Delays.
IEEE Trans. Syst. Man Cybern. Syst., 2020

2019
Multiple $\psi$ -Type Stability of Cohen-Grossberg Neural Networks With Both Time-Varying Discrete Delays and Distributed Delays.
IEEE Trans. Neural Networks Learn. Syst., 2019

Multiple $\psi$ -Type Stability and Its Robustness for Recurrent Neural Networks With Time-Varying Delays.
IEEE Trans. Cybern., 2019

2018
Multistability and instability analysis of recurrent neural networks with time-varying delays.
Neural Networks, 2018

2016
Multistability of recurrent neural networks with time-varying delays and nonincreasing activation function.
Neurocomputing, 2016


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