Stochastic Models, Information Theory, and Lie Groups, Volume 1: Classical Results and Geometric Methods

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Springer Science & Business Media, Sep 2, 2009 - Mathematics - 383 pages

This unique two-volume set presents the subjects of stochastic processes, information theory, and Lie groups in a unified setting, thereby building bridges between fields that are rarely studied by the same people. Unlike the many excellent formal treatments available for each of these subjects individually, the emphasis in both of these volumes is on the use of stochastic, geometric, and group-theoretic concepts in the modeling of physical phenomena.

Stochastic Models, Information Theory, and Lie Groups will be of interest to advanced undergraduate and graduate students, researchers, and practitioners working in applied mathematics, the physical sciences, and engineering. Extensive exercises and motivating examples make the work suitable as a textbook for use in courses that emphasize applied stochastic processes or differential geometry.

 

Contents

Introduction
1
Gaussian Distributions and the Heat Equation
31
Probability and Information Theory
62
Stochastic Differential Equations
101
Geometry of Curves and Surfaces
140
Differential Forms
193
Polytopes and Manifolds
233
Stochastic Processes on Manifolds
289
Summary
313
Review of Linear Algebra Vector Calculus and Systems Theory
315
References
360
Index
362
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