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- W2990296983 abstract "In this paper, we consider a class of quaternion-valued inertial neural networks with time-varying delays. First, by applying a continuation theorem of coincidence degree theory, we establish the existence of anti-periodic solutions of the considered neural networks. Second, by choosing a proper v ariable substitution, we transform the neural networks into a system of first order differential equations, and by constructing a suitable Lyapunov function, we derive a set of sufficient conditions ensuring the global exponential stability of the system. Finally, we give two examples to illustrate the effectiveness of our results." @default.
- W2990296983 created "2019-12-05" @default.
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- W2990296983 date "2019-12-23" @default.
- W2990296983 modified "2023-10-16" @default.
- W2990296983 title "Anti-periodic solutions for quaternion-valued inertial neural networks with time-varying delays1" @default.
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- W2990296983 doi "https://doi.org/10.3233/jifs-182731" @default.
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