Institute of Information Theory and Automation

Some Results and Problems in the Theory of Fisher Information

Lecturer: Abram Kagan
Institute: Dept. of Mathematics, Univ. of Maryland, College Park
Date and time: 23.11.2015 - 14:00
Room: 25
Department: Decision Making Theory (MTR)


After presenting general properties of the Fisher information, not so well known results in the signal plus noise model (Stam inequality, Carlen's superadditivity, contamination, small perturbations) will be discussed.

Close connections to parameter estimation, especially to the Pitman estimators will be demonstrated as well as properties of the latter.

Lower bounds for the Fisher information and the role of special distributions will be shown.

Institute of Information Theory and Automation