Neural network modelling of variable hystereticinductors

Abstract
A neural model for devices made using hysteretic materials is presented. The model provides a close prediction of dynamic hysteresis loops and accounts for dependencies on position. Traditional theoretical approach limitations and experimental results are discussed.

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