Exponential State Estimation and Passivity of Fuzzy Quaternion-Valued Memristive Neural Networks: Norm Approach

In this article, we consider exponential estimation and passivity of memristive neural networks with quaternion parameters. A Takagi–Sugeno type rule is introduced into the quaternion memristive neural networks, which makes the system much easier. To achieve the exponential stability of the estimation error system, a proper controller is designed, which derived in the two norm form. Further, the quasi-state estimation condition is also considered. Along with Lyapunov theory, some criteria are obtained to achieve the exponential passivity of the discussed system.