https://www.tau.ac.il/%7Eklafter1/258.pdf

The random walk's guide to anomalous diffusion: a fractional dynamics approach

The capacity of ad hoc wireless networks is constrained by the mutual interference of concurrent transmissions between nodes. We study a model of an ad hoc network where n nodes communicate in random source-destination pairs. These nodes are assumed to be mobile. We examine the per-session throughput for applications with loose delay constraints, such that the topology changes over the time-scale of packet delivery. Under this assumption, the per-user throughput can increase dramatically when nodes are mobile rather than fixed. This improvement can be achieved by exploiting a form of multiuser diversity via packet relaying.

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Mobility increases the capacity of ad hoc wireless networks

* Recasts topics in random fields by following a completely new way of handling both geometry and probability
 * Significant exposition of the work of others in the field
 * Presentation is clear and pedagogical
 * Excellent reference work as well as excellent work for self study

This monograph is devoted to a completely new approach to geometric problems arising in the study of random fields. The groundbreaking material in Part III, for which the background is carefully prepared in Parts I and II, is of both theoretical and practical importance, and striking in the way in which problems arising in geometry and probability are beautifully intertwined.

The three parts to the monograph are quite distinct. Part I presents a user-friendly yet comprehensive background to the general theory of Gaussian random fields, treating classical topics such as continuity and boundedness, entropy and majorizing measures, Borell and Slepian inequalities. Part II gives a quick review of geometry, both integral and Riemannian, to provide the reader with the material needed for Part III, and to give some new results and new proofs of known results along the way. Topics such as Crofton formulae, curvature measures for stratified manifolds, critical point theory, and tube formulae are covered. In fact, this is the only concise, self-contained treatment of all of the above topics, which are necessary for the study of random fields. The new approach in Part III is devoted to the geometry of excursion sets of random fields and the related Euler characteristic approach to extremal probabilities.

"Random Fields and Geometry" will be useful for probabilists and statisticians, and for theoretical and applied mathematicians who wish to learn about new relationships between geometry and probability. It will be helpful for graduate students in a classroom setting, or for self-study. Finally, this text will serve as a basic reference for all those interested in the companion volume of the applications of the theory. These applications, to appear in a forthcoming volume, will cover areas as widespread as brain imaging, physical oceanography, and astrophysics.

Random Fields and Geometry

The capacity of ad-hoc wireless networks is constrained by the mutual interference of concurrent transmissions between nodes. We study a model of an ad-hoc network where n nodes communicate in random source-destination pairs. These nodes are assumed to be mobile. We examine the per-session throughput for applications with loose delay constraints, such that the topology changes over the time-scale of packet delivery. Under this assumption, the per-user throughput can increase dramatically when the nodes are mobile rather than fixed. This improvement can be achieved by exploiting node mobility as a type of multiuser diversity.

Mobility increases the capacity of ad-hoc wireless networks

With the aim of modelling key stylized features of observational series from finance and turbulence a number of stochastic processes with normal inverse Gaussian marginals and various types of dependence structures are discussed. Ornstein-Uhlenbeck type processes, superpositions of such processes and stochastic volatility models in one and more dimensions are considered in particular, and some discussion is given of the feasibility of making likelihood inference for these models.

Processes of normal inverse Gaussian type

Stable non-Gaussian random processes , by G. Samorodnitsky and M. S. Taqqu. Pp. 632. £49.50. 1994. ISBN 0-412-05171-0 (Chapman and Hall).

problem, Hilbert's decision problem and Turing's halting problem as examples of the former. Definitions are given, each in terms of an algorithm, of the informal concepts of computable function, decidable relation and semi-decidable relation. The next two substantial chapters introduce, in turn, a machine model of computability and a mathematical model of computability. For the machine model Hodel presents the concept of Unlimited Register Machine (URM) rather than a Turing machine, which dates back to the paper Computability of Recursive Functions, published in 1963 by J. C. Sheperdson and H. E. Sturgis. Turing's argument for the unsolvability of the Halting Problem is given and how he exploited this to resolve the Decision Problem is sketched. The unsolvability of the Word Problem, originally given by Markov and Post, is proved in full as is the uncomputability of the busy beaver function.

Stochastic analysis and diffusion processes by G. Kallianpur and P. Sundar, pp 352, £65 (hbk), £29.99 (pbk) ISBN 978-0-965706-3, ISBN 978-0-965707-0, Oxford Graduate Texts in Mathematics 24, Oxford University Press (2014).

Dave Applebaum

Papers

Stable non-Gaussian random processes , by G. Samorodnitsky and M. S. Taqqu. Pp. 632. £49.50. 1994. ISBN 0-412-05171-0 (Chapman and Hall).

Stochastic analysis and diffusion processes by G. Kallianpur and P. Sundar, pp 352, £65 (hbk), £29.99 (pbk) ISBN 978-0-965706-3, ISBN 978-0-965707-0, Oxford Graduate Texts in Mathematics 24, Oxford University Press (2014).