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- W4297983849 abstract "This paper investigates the bifurcation issue of fractional-order four-neuron recurrent neural network with multiple delays. First, the stability and Hopf bifurcation of the system are studied by analyzing the associated characteristic equations. It is shown that the dynamics of delayed fractional-order neural networks not only depend heavily on the communication delay but also significantly affects the applications with different delays. Second, we numerically demonstrate the effect of the order on the Hopf bifurcation. Two numerical examples illustrate the validity of the theoretical results at the end." @default.
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- W4297983849 date "2022-09-29" @default.
- W4297983849 modified "2023-10-14" @default.
- W4297983849 title "Bifurcations of a Fractional-Order Four-Neuron Recurrent Neural Network with Multiple Delays" @default.
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- W4297983849 doi "https://doi.org/10.1155/2022/1779582" @default.
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