Exponential State Estimation Of Delayed Fuzzy Quaternion-Valued Inertial Neural Networks

This article delves into the exponential state estimation problem of fuzzy quaternion-valued inertial neural networks (FQVINNs) with time-varying delay. FQVINNs model is discussed as a whole without any decomposition and non-reduction method is adopted to analyze the second-order differential equations. Based on quadratic norm, suitable Lyapunov function is constructed. Then, by applying some inequality techniques, an algebraic criterion is derived to ensure the exponential stability of the estimation error system and achieve the state estimation for the considered model. Finally, a numerical example is given to verify the effectiveness of our result.