Aimed at students and researchers in mathematics, communications engineering, and economics, this book describes the probabilistic structure of a Gaussian process in terms of its canonical representation (or its innovation process). Multiple Markov properties of a Gaussian process and equivalence problems of Gaussian processes are clearly presented. The authors' approach is unique, involving causality in time evolution and information-theoretic aspects. Because the book is self-contained and only requires background in the fundamentals of probability theory and measure theory, it would be suitable as a textbook at the senior undergraduate or graduate level.
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Für höhere Schule und Studium
Für Beruf und Forschung
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ISBN-13
978-0-8218-4568-4 (9780821845684)
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Schweitzer Klassifikation
1. Foundations of probability theory and limit theorems; 2. Systems of Gaussian random variables; 3. Stationary Gaussian processes and their representations; 4. Canonical representation of Gaussian processes{rm: }general theory and multiplicity; 5. Multiple Markov Gaussian processes; 6. Equivalence of Gaussian processes; 7. Stochastic integrals and martingales; VSKIP-1PT
