In design of experiments for nonlinear regression model identification, the design criterion depends on the unknown parameters to be identified. Classical strategies consist in ...
H. ElAbiad, Laurent Le Brusquet, Marie-Eve Davoust
Linear parameterized models of optical flow, particularly affine models, have become widespread in image motion analysis. The linear model coefficients are straightforward to estim...
David J. Fleet, Michael J. Black, Yaser Yacoob, Al...
This paper presents a comprehensive formulation of a linearized state space process model for a generic two-reactant-two-product reactive distillation system. The development of t...
In a reverberant scenario, phase transformed weighted algorithms are more robust than Maximum Likelihood (ML) because of the insufficiency of the data model to incorporate reverb...
Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much ...
Benjamin Chain, Helen Bowen, John Hammond, Wilfrie...