A method of incorporating experience in iterative learning controllers is proposed in this paper. Importance of the selection of initial control input in the convergence of error is highlighted. It is proposed that if previous experience of the controller can be incorporated in the selection of the initial control input for a new desired trajectory tracking task, the convergence of error can be...

Trajectory classification, i.e., model construction for predicting the class labels of moving objects based on their trajectories and other features, has many important, real-world applications. A number of methods have been reported in the literature, but due to using the shapes of whole trajectories for classification, they have limited classification capability when discriminative features a...

An important part of extra-tropical stratosphereto-troposphere transport occurs in association with baroclinic wave breaking and cut-off decay at the tropopause. In the last decade many studies have attempted to estimate stratospheretroposphere exchange (STE) in such synoptic events with various methods, and more recently efforts have been made to inter-compare these methods. These inter-compar...

When humans navigate a crowed space such as a university campus or the sidewalks of a busy street, they follow common sense rules based on social etiquette. In this paper, we argue that in order to enable the design of new algorithms that can take fully advantage of these rules to better solve tasks such as target tracking or trajectory forecasting, we need to have access to better data in the ...

In this paper, we propose an efficient signature-based indexing scheme for efficiently dealing with the trajectories of current moving objects on road networks. We show that our indexing scheme achieves much better trajectory retrieval performance than the existing trajectory indexing schemes, such as TB-tree, FNR-tree and MON-tree.