The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares… (More)
This paper introduces a new robust nonlinear identification algorithm using the predicted residual sums of squares (PRESS) statistic and forward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the… (More)
—In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on… (More)
— The following presents a standardized approach to the kinematics of a generalized stereo robot head, providing both forward and inverse kinematic solutions as well as a discussion on the head Jacobian. The paper is intended as a comprehensive tutorial and as a standard notation reference for researchers in the field of active vision.
This paper proposes a solution to the problems associated with network latency in multiuser , distributed virtual environments (DVE's). It begins by comparing DVE's with synchronised host clocks against unsynchronised host clocks. A hybrid solution is described, which combines the advantages of both synchronised and unsynchronised models, using the concept… (More)