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    Generic ESD Generator Model using Artificial Neural Network

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    Date
    2021-07
    Type
    Article
    Author
    Yousaf, Jawad
    Javed, Kamran
    Ghazal, Mohammed
    ETAL.
    Metadata
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    Abstract
    Different commercial ESD gun models, although complying with the standard ESD waveform requirements in terms of rise time and current values for standard Pellegrini target, produce different ESD waveforms. The variations of the ESD source and target impedance in real-time with the change in the gun model affects the ESD susceptibility compliance testing results and immunity analysis for the estimation of possible ESD failure in a product. This study presents, for the first time, a novel generic ESD generator model using artificial neural network (ANN) based deep learning techniques. The developed deep learning model incorporates the characteristics of the real-time generated ESD waveforms by various commonly used commercial ESD gun models with different target load impedances. The presented model could be used as a generic ESD source for fast ESD susceptibility and immunity testing’s at the design stage of a product using numerical or circuit-analysis-based tools
    URI
    https://dspace.adu.ac.ae/handle/1/2663
    DOI
    https://doi.org/10.1109/EMC/SI/PI/EMCEurope52599.2021.9559290
    Citation
    Yousaf, J., Javed, K., & Ghazal, M. (2021, July). Generic ESD Generator Model using Artificial Neural Network. In 2021 IEEE International Joint EMC/SI/PI and EMC Europe Symposium (pp. 1000-1005). IEEE.
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