The EPI principle builds on the well known idea that the observation of a "source" phenomenon is never completely accurate. That is, information present in the source is inevitably lost when observing the source. The random errors in the observations are presumed to define the probability distribution function of the source phenomenon. That is, "the physics lies in the fluctuations." The information loss is postulated to be an extreme value. Denoting the Fisher information in the data as, and that in the source as, the EPI principle states that Since the data are generally imperfect versions of the source, the extremum for most situations is a minimum. Thus there is a comforting tendency for any observation to describe its source faithfully. The EPI principle may be solved for the unknown system amplitudes via the usual Euler-Lagrange equations of variational calculus.
Books
Frieden, B. Roy - Physics from Fisher Information: A Unification , 1st Ed. Cambridge University Press,, pp328, 1998
Frieden, B. Roy - Science from Fisher Information: A Unification , 2nd Ed. Cambridge University Press,, pp502, 2004
Frieden, B.R. & Gatenby, R.A. eds. - Exploratory Data Analysis Using Fisher Information, Springer-Verlag, pp358, 2006
Recent papers using EPI
Anton, M. & Weisen, H. & Dutch, M.J. - "X-ray tomography on the TCV tokamak", Plasma Phys. Control. Fusion 38, 1849-1878, 1996 http://ej.iop.org/links/q80/fVFo+Bx3KRlwd6qcdU2Saw/p61101.pdf
Mlynar, J. & Bertalot, L. - "Neutron spectra unfolding with minimum Fisher regularization" http://pos.sissa.it/archive/conferences/025/063/FNDA2006_063.pdf Subj: Diagnosis of plasma shape within the tokamak fusion machine using reconstructions based upon EPI.
Venkatesan, Ravi. - "Information encryption using a Fisher-Schrödinger Model", Presented at 6th International Conference on Complex Systems June, 2006 Boston, Massachusetts Full paper is in Frieden and Gatenby, 2006 http://necsi.edu/community/wiki/index.php/ICCS06/235 Subj: Encryption, secure transmission using EPI, in particular game aspect.
Fath B.D. & Cabezas, H. & CW Pawlowski - "Exergy and Fisher information as ecological indices",
Yolles. M.I. - "Knowledge Cybernetics: A New Metaphor for Social Collectives", 2005
Venkatesan, R.C. - "Invariant Extreme Physical Information and Fuzzy Clustering", Proc. SPIE Symposium on Defense & Security,
Ménard, Michel. & Dardignac, Pierre-André. & Chibelushi, Claude C. - "Non-extensive thermostatistics and extreme physical information for fuzzy clustering ", IJCC, 2 : 1-63, 2004 http://www.yangsky.us/ijcc/pdf/ijcc241.pdf