This paper presents a preliminary version of a probabilistic model for the uncertainty quantification of complex electronic systems resulting from the combination of the leastsquares support vector machine (LS-SVM) and the Gaussian process (GP) regression. The proposed model, trained with a limited set of training pairs provided by a set of full-wave expensive simulations, is adopted for the prediction of the efficiency of an integrated voltage regulator (IVR) with 8 uniformly distributed random parameters. The accuracy and the feasibility of the proposed model have been investigated by comparing the model predictions and its confidence intervals with the results of a Monte Carlo (MC) full-wave simulation of the device.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Networks and Communications
- Electrical and Electronic Engineering