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- W2602119095 abstract "Field computation in media exhibiting hysteresis is crucial to a variety of applications such as magnetic recording processes and accurate determination of core losses in power devices. Recently, Hopfield neural networks (HNN) have been successfully configured to construct scalar and vector hysteresis models. This paper presents an efficient hysteresis modeling methodology and its implementation in field computation applications. The methodology is based on the application of the integral equation approach on discretized triangular magnetic sub-regions. Within every triangular sub-region, hysteresis properties are realized using a 3-node HNN. Details of the approach and sample computation results are given in the paper." @default.
- W2602119095 created "2017-04-07" @default.
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- W2602119095 date "2017-07-01" @default.
- W2602119095 modified "2023-10-12" @default.
- W2602119095 title "An efficient hysteresis modeling methodology and its implementation in field computation applications" @default.
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- W2602119095 doi "https://doi.org/10.1016/j.jmmm.2017.03.042" @default.
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