Abstract: This paper proposes an innovative event-triggered relearning strategy for neural network modeling, to enhance prediction accuracy under the non-stationary and variable conditions frequently ...
Abstract: We develop a charge deficit-based non-quasi-static (NQS) model that is compatible with neural network-based transistor compact models for transient, AC, and RF simulations. The charge ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback