Puhalskii Large Deviations and Idempotent Probability

Erscheinungsjahr 2010
ISBN: 978-1-4200-3580-3
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 520 Seiten

Reihe: Monographs and Surveys in Pure and Applied Mathematics

In the view of many probabilists, author Anatolii Puhalskii's research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the connections between the large deviation principle (LDP) and well-known methods for establishing weak convergence results.

Large Deviations and Idempotent Probability expounds upon the recent methodology of building large deviation theory along the lines of weak convergence theory. The author develops an idempotent (or maxitive) probability theory, introduces idempotent analogues of martingales (maxingales), Wiener and Poisson processes, and Ito differential equations, and studies their properties. The large deviation principle for stochastic processes is formulated as a certain type of convergence of stochastic processes to idempotent processes. The author calls this large deviation convergence.

The approach to establishing large deviation convergence uses novel compactness arguments. Coupled with the power of stochastic calculus, this leads to very general results on large deviation asymptotics of semimartingales. Large and moderate deviation asymptotics are treated in a unified manner.

Starting with the foundations of idempotent measure theory and culminating in applications to large deviation asymptotics of queueing systems, Large Deviations and Idempotent Probability offers an outstanding opportunity to examine both the development of a remarkable approach and recently discovered results as presented by one of the foremost leaders in the field.

Zielgruppe

Researchers and graduate students of probability theory, mathematical statistics, statistical physics, and communication networks

Autoren/Hrsg.

Puhalskii, Anatolii

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Allgemeines Enzyklopädien, Nachschlagewerke, Wörterbücher
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

IDEMPOTENT PROBABILITY THEORY
Idempotent Probability Measures
Idempotent Measures
Measurable Maps
Modes of Convergence
Idempotent Integration
Product Spaces
Independence and Conditioning
Idempotent Distributions and Laplace-Fenchel Transforms'
Idempotent Measures on Topological Spaces
Idemptent Measures on Projective Limits
Topological Spaces of Idempotent Probabilities
Maxingales
Stopping Times
Idempotent Stochastic Processes
Exponential Maxingales
Wiener and Poisson Idempotent Processes
Continuous Local Maxingales
Idempotent Ito Equations
Semimaxingales and Maxingale Problems
Proofs of the Uniqueness Results
Convergence of Idempotent Processes
LARGE DEVIATION CONVERGENCE
Large Deviation Convergence in Tihonov Spaces
General Theory
Large Deviation Convergence in the Skorohod Space
The Method of Finite-Dimensional Distributions
Convergence of Stochastic Exponentials
LD Convergence via Convergence of the Characteristics
Corollaries
The Method of the Maxingale Problem
Convergence of Stochastic Exponentials
Convergence of Characteristics
APPLICATIONS
Markov Processes
Queueing Networks
APPENDIX