Abstract

With the introduction of quaternion number and memristor connection weights, the quaternion-valued memristive neural networks (QVMNNs) is then constructed. Based on the differential theory and quaternion feature, the finite-time boundedness problem of QVMNNs is considered in both quaternion area and complex area. Theorems for guaranteeing finite-time boundedness of QVMNNs are achieved by appropriately choosing the Lyapunov functional and applying linear matrix inequality (LMI). Finally, a simulation example is presented to demonstrate our results.

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