MOTIVATION In vitro and in vivo selection of vaccines is time consuming, expensive and the selected vaccines may not be able to provide protection against broad-spectrum viruses because of emerging antigenically novel disease strains. A powerful computational model that incorporates these protein/DNA or RNA level fluctuations can effectively predict antigenically variant strains, and can minimi...

Traditionally multivariate calibration models have been developed using regression based techniques including principal component regression and partial least squares and their non-linear counterparts. This paper proposes the application of Gaussian process regression as an alternative method for the development of a calibration model. By formulating the regression problem in a probabilistic fr...

In this paper we present an approach to modeling the non-linearities of analog electronic components using time-variant digital linear filters. The filter coefficients are computed at every sample depending on the current state of the system. With this technique we are able to accurately model an analog filter including a nonlinear inductor with a saturating core. The value of the magnetic perm...