A MHO-based magnetic hysteresis model for amorphous materials

A magnetic hysteretic operator (MHO) is proposed in this paper. Based on the constructed MHO, the input space of neural networks is expanded from one-dimension to two-dimension using the expanded space method so that the one-to-multiple mapping of magnetic hysteresis is transformed into one-to-one mapping. Based on the expanded input space, a neural network is employed to identify magnetic hysteresis. The result of an experimental example suggests the proposed approach is effective.