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• W3036367681 abstract "Summary In this article, a general class of delayed interval inertial Cohen‐Grossberg neural networks described by quaternion‐valued parameters is considered. Under the homeomorphism mapping theory and lexicographical order method, we investigate the exponential stabilization problem for the quaternion‐valued Cohen‐Grossberg neural networks. To do so, we verify the existence and uniqueness of the equilibrium point (EP), and then by designing a sampled‐data feedback controller, several sufficient criteria are derived to ascertain the robust stability of the EP for the given system. What should be mentioned is that the state parameters are taking values in an interval, which implies the states are taking values between two different quaternions, thus, a lexicographical order method is employed, which proposed an effective method to determine the “magnitude” of two different quaternions. Finally, numerical example is provided to demonstrate the effectiveness of the developed theoretical results." @default.
• W3036367681 created "2020-06-25" @default.
• W3036367681 creator A5017808266 @default.
• W3036367681 creator A5062763600 @default.
• W3036367681 date "2020-06-17" @default.
• W3036367681 modified "2023-10-13" @default.
• W3036367681 title "Exponential stabilization of inertial quaternion‐valued Cohen‐Grossberg neural networks: Lexicographical order method" @default.
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• W3036367681 doi "https://doi.org/10.1002/rnc.5049" @default.
• W3036367681 hasPublicationYear "2020" @default.
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