Li, Ruoxia; Cao, Jinde Exponential stabilization of inertial quaternion-valued Cohen-Grossberg neural networks: lexicographical order method. (English) Zbl 1466.93132 Int. J. Robust Nonlinear Control 30, No. 13, 5205-5220 (2020). 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. Cited in 2 Documents MSC: 93D23 Exponential stability 93D21 Adaptive or robust stabilization 93B70 Networked control 93C57 Sampled-data control/observation systems 93B52 Feedback control Keywords:Cohen-Grossberg neural networks; inertial terms; lexicographical order; quaternion-valued; robust stabilization PDFBibTeX XMLCite \textit{R. Li} and \textit{J. Cao}, Int. J. Robust Nonlinear Control 30, No. 13, 5205--5220 (2020; Zbl 1466.93132) Full Text: DOI