Book contents
- Frontmatter
- Contents
- Preface
- Chapter 1 Introduction
- Chapter 2 The toolbox
- Chapter 3 Markov and Frobenius–Perron operators
- Chapter 4 Studying chaos with densities
- Chapter 5 The asymptotic properties of densities
- Chapter 6 The behavior of transformations on intervals and manifolds
- Chapter 7 Continuous time systems: an introduction
- Chapter 8 Discrete time processes embedded in continuous time systems
- Chapter 9 Entropy
- Chapter 10 Stochastic perturbation of discrete time systems
- Chapter 11 Stochastic perturbation of continuous time systems
- References
- Notation and symbols
- Index
Preface
Published online by Cambridge University Press: 05 March 2012
- Frontmatter
- Contents
- Preface
- Chapter 1 Introduction
- Chapter 2 The toolbox
- Chapter 3 Markov and Frobenius–Perron operators
- Chapter 4 Studying chaos with densities
- Chapter 5 The asymptotic properties of densities
- Chapter 6 The behavior of transformations on intervals and manifolds
- Chapter 7 Continuous time systems: an introduction
- Chapter 8 Discrete time processes embedded in continuous time systems
- Chapter 9 Entropy
- Chapter 10 Stochastic perturbation of discrete time systems
- Chapter 11 Stochastic perturbation of continuous time systems
- References
- Notation and symbols
- Index
Summary
This book is about densities. In the history of science, the concept of densities emerged only recently as attempts were made to provide unifying descriptions of phenomena that appeared to be statistical in nature. Thus, for example, the introduction of the Maxwellian velocity distribution rapidly led to a unification of dilute gas theory; quantum mechanics developed from attempts to justify Planck's ad hoc derivation of the equation for the density of blackbody radiation; and the field of human demography grew rapidly after the introduction of the Gompertzian age distribution.
From these and many other examples, as well as the formal development of probability and statistics, we have come to associate the appearance of densities with the description of large systems containing inherent elements of uncertainty. Viewed from this perspective one might find it surprising to pose the question: “What is the smallest number of elements that a system must have, and how much uncertainty must exist, before a description in terms of densities becomes useful and/or necessary?” The answer is surprising, and runs counter to the intuition of many. A one-dimensional system containing only one object whose dynamics are completely deterministic (no uncertainty) can generate a density of states! This fact has only become apparent in the past half-century due to the pioneering work of E. Borel [1909], A. Renyi [1957], and S. Ulam and J. von Neumann. These results, however, are not generally known outside that small group of mathematicians working in ergodic theory.
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- Information
- Probabilistic Properties of Deterministic Systems , pp. ix - xPublisher: Cambridge University PressPrint publication year: 1985