A neural networks based model of inverse hysteresis

A novel and simple approach based on transformation using neural networks is proposed in this paper to model the inverse behavior of hysteresis. In this approach, a continuous transformation is used to construct an elementary inverse hysteresis operator (EIHO), which can extract the change tendency...

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Veröffentlicht in:	Physica. B, Condensed matter Condensed matter, 2011-11, Vol.406 (21), p.4109-4114
Hauptverfasser:	Ma, Lianwei, Tan, Yonghong, Shen, Yu
Format:	Artikel
Sprache:	eng
Schlagworte:	Condensed matter: electronic structure, electrical, magnetic, and optical properties Continuous transformation Dielectrics, piezoelectrics, and ferroelectrics and their properties Elementary inverse hysteresis operator Exact sciences and technology Inverse hysteresis Neural network Physics Piezoelectricity and electromechanical effects
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