In this paper the performance and the accuracy of artificial neural networks for the prediction of high-speed digital interconnects up to 100 GHz on printed circuit boards are analyzed and evaluated. The prediciton accuracy is evaluated both for …
Anwendung von Methoden des maschinellen Lernens zur Vorhersage des Einflusses kleiner organischer Additive auf das Degradationsverhalten von Magnesium
Currently machine learning tools are not capable to provide analysis solutions for complex printed circuit boards. It is unknown how to prepare the data and how to determine the optimal architecture of the machine learning process. We show that both …
The vast number of small molecules with potentially useful dissolution modulating properties (inhibitors or accelerators) renders currently used experimental discovery methods time- and resource-consuming. Fortunately, emerging computer-assisted …
An artificial neural network approach is presented to predict whether a power delivery network setup violates the target impedance. Random decoupling capacitor distributions are evaluated. It is shown that a prediction accuracy close to 90% can be …