Fixed-Time Synchronization and Energy Consumption Prediction of Interconnected Memristive Neural Networks with Discontinuous Activation Functions

In this paper, the fixed-time synchronization (FXTS) and energy consumption prediction of interconnected memristive neural networks (IMNNs) with discontinuous activation functions are studied. First of all, to deal with discontinuous activation functions, a unified discontinuous controller, which can be applied to other networks, is designed to effectuate FXTS. Based on Lyapunov stability theory, some sufficient conditions for the synchronization of IMNNs are given, and the settling-time is estimated. Meanwhile, to accurately evaluate engineering costs, the energy consumption of the system control process is obtained, and the influence of specific controller parameters on energy consumption is analyzed. Finally, a numerical simulation is presented to verify the correctness of the results.