A new computer-aided multi-dimensional device modeling algorithm based on binning concepts

Accurate modeling of devices is critical to efficient computer aided design and optimization. Commonly encountered modeling techniques include empirical formulae, equivalent circuits, and black-box models. Important criteria in device modeling are model accuracy, computational simplicity, generality of the modeling approach, etc. In this paper, we present a multi-dimensional CAD algorithm to device modeling based on a concept often referred to as binning. For a given set of data either from measurements or simulations, the proposed algorithm leads to an accurate model comprising of a set of sub-models with best possible accuracy, while keeping the model structure simple. The algorithm is general and can be applied in the context of any black-box modeling technique; however, we demonstrate multi-dimensional neural modeling of active and passive components. Resulting models are shown to exhibit relatively better accuracies compared to those developed via standard modeling approaches.