Applied Statistical Decision Theory.

Statistical Decision Fusion Theory

By combining information theory, statistical decision theory, and maximum entropy to address the decision fusion problems, a statistical decision fusion theory is obtained. The theory explains why decision fusion is so difficult and why the performance of decision fusion systems does not always meet expectations. The theory suggests how statistical decision systems such as the conceptual "Famil...

Statistical decision theory and evolution.

Two recent articles by Geisler and Diehl use Bayesian statistical decision theory to model the co-evolution of predator and prey in a simple, game-like environment. The prey is characterized by its coloration. The predator is characterized by the chromatic sensitivity of its visual system and its willingness to attack. The authors demonstrate how the coloration of prey and the perceptual system...

Statistical Decision and Learning Theory

This paper reviews and contrasts the basic elements of statistical decision theory [1–4] and statistical learning theory [5–7]. It is not intended to be a comprehensive treatment of either subject, but rather just enough to draw comparisons between the two. Throughout this paper, let X denote the input to a decision-making process and Y denote the correct response or output (e.g., the value of ...

Statistical Decision Theory: Concepts, Methods and Applications

Evolving Neural Networks for Statistical Decision Theory

Acknowledgements I want to express sincere thanks to my advisor Mgr. Radoslav Harman, PhD. for his careful supervision , stimulating discussions and inspiring ad-vices. I would also like to thank Doc. MUDr. Juraj Pavlásek, DrSc. for introducing me to addressed domain and Nuno Cavalheiro Marques, PhD. for his comments. Finally, I am very grateful to my family and friends for supporting me during...