VIII, 265 p. 24 illus., 15 illus. in color., online resource.
SERIES
Series Title
(Springer Proceedings in Mathematics & Statistics,2194-1009
Volume Designation
; 53)
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Electronic
CONTENTS NOTE
Text of Note
Random Matrices are one of the major research areas in modern probability theory, due to their prominence in many different fields such as nuclear physics, statistics, telecommunication, free probability, non-commutative geometry, and dynamical systems. A great deal of recent work has focused on the study of spectra of large random matrices on the one hand and on iterated random functions, especially random difference equations, on the other. However, the methods applied in these two research areas are fairly dissimilar. Motivated by the idea that tools from one area could potentially also be helpful in the other, the volume editors have selected contributions that present results and methods from random matrix theory as well as from the theory of iterated random functions. This work resulted from a workshop that was held in M?╝nster, Germany in 2011. The aim of the workshop was to bring together researchers from two fields of probability theory: random matrix theory and the theory of iterated random functions. Random matrices play fundamental, yet very different roles in the two fields. Accordingly, leading figures and young researchers gave talks on their field of interest that were also accessible to a broad audience.
Text of Note
E. Le Page: Tails of a stationary probability measure for an affine stochastic recursion on the line -- Yv. Guivarc'h: On homogeneity at infinity of stationary measures for affine stochastic recursions -- M. Stolz: Limit theorems for random elements of the compact classical groups -- T. Kriecherbauer: Universality of local eigenvalue statistics -- R. Speicher: Asymptotic eigenvalue distribution of random matrices and free stochastic analysis -- M. Peign?ش: Conditioned random walk in Weyl chambers and renewal theory in a cone -- D. Buraczewski: The linear stochastic equation R =_d \sum_1=i
SERIES
Title
Springer Proceedings in Mathematics & Statistics,2194-1009