Hierarchical Clustering for TLP ESD Characterization of Multi-Finger ggNMOSTs

We propose a characterization method for evaluating the ESD behavior of multi-finger Grounded Gate NMOS or ggNMOS transistors using TLP stress data ($\mathrm{V}, \mathrm{I}, I_{\text {leak }}$). By employing a hierarchical clustering with Mahalanobis distance, the approach addresses challenges in analyzing data with noise and variability using real-world techniques, such as conventional Transmission Line Pulsing (TLP) testing platform. The proposed method enhances data integrity by identifying and excluding the unexpected behavior of samples caused by measurement or setup issues while providing statistical analyses the characterization of the devices that demonstrate normal behavior.