Power-Rate Synchronization of Fractional-Order Nonautonomous Neural Networks with Heterogeneous Proportional Delays

This paper is concerned with the problem of global power-rate synchronization of fractional-order nonautonomous neural networks with heterogeneous proportional delays. By utilizing the Leibniz rule for fractional differentiation and an extended comparison technique, delay-dependent conditions are derived to ensure that the considered fractional-order neural network model is globally synchronous with a power decaying rate. Two examples with numerical simulations are given to demonstrate the effectiveness of the obtained results.