Posted by **libr** at Dec. 10, 2015

English | 2001-01-20 | ISBN: 0821805312 | 206 pages | DJVU | 4.7 mb

Posted by **interes** at Nov. 23, 2013

English | 2001-01-20 | ISBN: 0821805312 | 206 pages | DJVU | 4.7 mb

Information geometry provides the mathematical sciences with a new framework of analysis. It has emerged from the investigation of the natural differential geometric structure on manifolds of probability distributions, which consists of a Riemannian metric defined by the Fisher information and a one-parameter family of affine connections called the $\alpha$-connections.

Posted by **roxul** at Nov. 7, 2017

English | ISBN: 9814699756 | 2015 | 222 pages | PDF | 3 MB

Posted by **step778** at March 5, 2015

1953 | pages: 342 | ISBN: 0521467756 | PDF | 3,2 mb

Posted by **step778** at March 4, 2015

1953 | pages: 444 | ISBN: 0521469007 | DJVU | 5,3 mb

Posted by **ChrisRedfield** at Feb. 10, 2014

Published: 2011-06-26 | ISBN: 9400702043 | PDF | 288 pages | 3 MB

Posted by **hill0** at Sept. 27, 2017

English | 20 Sept. 2017 | ISBN: 3319564773 | 420 Pages | EPUB | 9.42 MB

The book provides a comprehensive introduction and a novel mathematical foundation of the field of information geometry with complete proofs and detailed background material on measure theory, Riemannian geometry and Banach space theory.

Posted by **AvaxGenius** at Sept. 6, 2017

English | PDF | 2017 | 411 Pages | ISBN : 3319564773 | 4.5 MB

The book provides a comprehensive introduction and a novel mathematical foundation of the field of information geometry with complete proofs and detailed background material on measure theory, Riemannian geometry and Banach space theory. Parametrised measure models are defined as fundamental geometric objects, which can be both finite or infinite dimensional.

Posted by **tukotikko** at March 7, 2016

2016 | 390 Pages | ISBN: 4431559779 | EPUB | 6 MB

Posted by **Underaglassmoon** at Feb. 5, 2016

Springer | Geometry & Topology | March 4, 2016 | ISBN-10: 4431559779 | 373 pages | pdf | 6.14 mb

Authors: Amari, Shun-ichi

Includes hot topics of applications to machine learning, signal processing, neural networks, and optimization

Applies information geometry to statistical inference and time-series analysis