Fixed Time Synchronization of Fuzzy Competitive Neural Networks
Abstract
(ST) are ob- tained by means of some special functions. Two kinds of the fixed-time control schemes are proposed and two forms of Lyapunov
function are constructed based on p-norm and 2-norm to discuss the fixed-time synchronization of CNNs. Furthermore, the efect of time scale
on the fixed-time synchronization of CNNs is considered. The results show that compared with the pre- vious researches, this paper provides a
smaller upper bound.
Keywords
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[1] Wang P, Li X, Lu J, et al. Fixed-Time Synchronization of Stochastic Complex-Valued Fuzzy Neural Networks with Memristor and Proportional Delays. Neural Processing Let- ters, 2023: 1-17. https://doi.org/10.1007/s11063-023-11320-2
[2] Qin X, Wang C, Li L, et al. Finite-time projective synchronization of memristor-based neural networks with leakage and time-varying
delays. Physica A, 2019, 531: 121788. https://doi.org/10.1016/j.physa.2019.121788
[3] Feng L, Hu C, Yu J, et al. Fixed-time synchronization of coupled memristive complex-valued neural networks. Chaos, Solitons Fractals,
2021, 148: 110993. http- s://doi.org/10.1016/j.chaos.2021.110993
[4] Ren H, Peng Z, Gu Y. Fixed-time synchronization of stochastic memristor-based neural networks with adaptive control. Neural Networks, 2020, 130: 165-175. http- s://doi.org/10.1016/j.neunet.2020.07.002
[5] Jia T, Chen X, Zhao F, et al. Adaptive fixed-time synchronization of s- tochastic memristor-based neural networks with discontinuous
activations and mixed delays. Journal of the Franklin Institute, 2023, 360(4): 3364-3388. http- s://doi.org/10.1016/j.jfranklin.2022.11.006
DOI: http://dx.doi.org/10.70711/frim.v3i4.6457
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