A neural model of hysteresis in amorphous materials and piezoelectric materials
Source abstract
Abstract
A new approach to constructing hysteretic operator (HO) is proposed in this paper. Based on the HO, the input space of neural networks is expanded from one-dimension to two-dimension and the multi-value mapping of hysteresis is transformed into a continuous mapping comprised of one-to-one mapping and multiple-to-one mapping. Based on the expanded input space, a neural network is employed to approximate hysteresis. The results of experimental examples suggest the proposed approach is effective.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Piezoelectric Actuators and Control · Neural Networks and Applications · Advanced Measurement and Metrology Techniques
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References (10)
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