A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning con...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
The ability to associate objects across multiple views allows co-operative use of an ensemble cameras for scene understanding. In this paper, we present a principled solution to o...
In this paper, we propose a framework called CC-Buddy, for maintaining dynamic data coherency in peer-to-peer environment. Working on the basis of peer heterogeneity in data coher...