Stochastic Models, Information Theory, and Lie Groups, Volume 2: Analytic Methods and Modern Applications

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Springer Science & Business Media, 16.11.2011 - 435 Seiten

The subjects of stochastic processes, information theory, and Lie groups are usually treated separately from each other. This unique two-volume set presents these topics 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.

Volume 2 builds on the fundamentals presented in Volume 1, delving deeper into relationships among stochastic geometry, geometric aspects of the theory of communications and coding, multivariate statistical analysis, and error propagation on Lie groups. Extensive exercises, motivating examples, and real-world applications make the work suitable as a textbook for use in courses that emphasize applied stochastic processes or differential geometry.

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.

 

Inhalt

Introduction and Examples
1
DifferentialGeometric Properties
55
Integration Convolutionand Fourier Analysis
79
13 Variational Calculus on Lie Groups
128
14 Statistical Mechanics and Ergodic Theory
155
15 Parts Entropy and the Principal Kinematic Formula
187
16 Multivariate Statistical Analysis and Random Matrix Theory
229
17 Information Communication and Group Theory
271
18 Algebraic and Geometric Coding Theory
313
19 Information Theory on Lie Groups
337
20 Stochastic Processes on Lie Groups
360
21 Locomotion and Perception as Communication over Principal Fiber Bundles
389
22 Summary
411
Index
419
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