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- W2728012017 abstract "In this paper, the global exponential stability for recurrent neural networks (QVNNs) with asynchronous time delays is investigated in quaternion field. Due to the non-commutativity of quaternion multiplication resulting from Hamilton rules: ij=−ji=k, jk=−kj=i, ki=−ik=j, ijk=i2=j2=k2=−1, the QVNN is decomposed into four real-valued systems, which are studied separately. The exponential convergence is proved directly accompanied with the existence and uniqueness of the equilibrium point to the consider systems. Combining with the generalized ∞-norm and Cauchy convergence property in the quaternion field, some sufficient conditions to guarantee the stability are established without using any Lyapunov–Krasovskii functional and linear matrix inequality. Finally, a numerical example is given to demonstrate the effectiveness of the results." @default.
- W2728012017 created "2017-07-14" @default.
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- W2728012017 date "2017-10-01" @default.
- W2728012017 modified "2023-10-13" @default.
- W2728012017 title "Decomposition approach to the stability of recurrent neural networks with asynchronous time delays in quaternion field" @default.
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- W2728012017 doi "https://doi.org/10.1016/j.neunet.2017.06.014" @default.
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