๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Methods of Information Geometry

โœ Scribed by Shun-Ichi Amari, Hiroshi Nagaoka


Book ID
127433518
Publisher
American Mathematical Society
Year
2000
Tongue
English
Weight
2 MB
Series
Translations of mathematical monographs 191
Category
Library
City
Providence, RI
ISBN
0821805312
ISSN
0065-9282

No coin nor oath required. For personal study only.

โœฆ Synopsis


Information geometry, which began as an investigation of the natural differential geometric structure possessed by families of probability distributions, is offered here in a complete treatment, translated from the original 1993 work in Japanese. The topic is applicable to information theory, stochastic processes, and systems, including neurocomputing. The authors, who assume some knowledge of statistics, systems theory and information theory, begin with an introduction to differential geometry and the theory of dual connections, before describing statistical inference, geometry of time series and linear systems, multiterminal information theory and statistical inference, information geometry for quantum systems, concluding with a grab-bag of applications including geometry of convex analysis, linear programming and gradient flows, neuro-manifolds and nonlinear systems, lie groups and transformation models.


๐Ÿ“œ SIMILAR VOLUMES


Methods of information geometry
โœ Shun-Ichi Amari, Hiroshi Nagaoka ๐Ÿ“‚ Library ๐Ÿ“… 2000 ๐Ÿ› American Mathematical Society ๐ŸŒ English โš– 1 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

Informal geometry
โœ Sam Creswell ๐Ÿ“‚ Article ๐Ÿ“… 1986 ๐Ÿ› National Council of Teachers of Mathematics โš– 287 KB
Methods of Algebraic Geometry
โœ TODD, J. A. ๐Ÿ“‚ Article ๐Ÿ“… 1948 ๐Ÿ› Nature Publishing Group ๐ŸŒ English โš– 125 KB
Geometry of Information Retrieval
โœ Rijsbergen C. J. ๐Ÿ“‚ Library ๐Ÿ“… 2005 ๐ŸŒ English โš– 1 MB

In his third book on information retrieval, Van Rijsbergen takes readers through a number of models for it, including a vector space model, a probabilistic model, and a logical model. He shows how these and others can be described and represented in Hilbert space, formulates the reasoning within eac