Abstract— Typical nonlinear model order reduction approaches need to address two issues: reducing the order of the model, and approximating the vector field. In this paper we fo...
In this paper, we present a simple analytical equation for capturing phase errors in 3-stage ring oscillators. The model, based on a simple but useful idealization of the ring osc...
This paper describes a probabilistic method of aligning and merging range images. We formulate these issues as problems of estimating the maximum likelihood. By examining the erro...
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...