Random matrix theory is now a big subject with applications in many disciplines of science, engineering and finance. This article is a survey specifically oriented towards the needs and …
ST Belinschi, T Mai, R Speicher - Journal für die reine und …, 2017 - degruyter.com
We develop an analytic theory of operator-valued additive free convolution in terms of subordination functions. In contrast to earlier investigations our functions are not just given …
C Qin, LJ Colwell - Proceedings of the National Academy of …, 2018 - National Acad Sciences
Covariance analysis of protein sequence alignments uses coevolving pairs of sequence positions to predict features of protein structure and function. However, current methods …
A bstract We show that in a general\(\mathcal {N}={1}\) supergravity with N≫ 1 scalar fields, an exponentially small fraction of the de Sitter critical points are metastable vacua. Taking …
The author presents a unified treatment of this highly interdisciplinary topic to help define the notion of cognitive radio. The book begins with addressing issues such as the fundamental …
We study random graphs with arbitrary distributions of expected degree and derive expressions for the spectra of their adjacency and modularity matrices. We give a complete …
Abstract Principal Component Analysis (PCA) is a classical method for reducing the dimensionality of data by projecting them onto a subspace that captures most of their …
In the context of cellular systems, it has been shown that multicell processing can eliminate inter-cell interference and provide high spectral efficiencies with respect to traditional …
O Ajanki, T Krüger, L Erdős - Communications on Pure and …, 2017 - Wiley Online Library
Let S be a positivity‐preserving symmetric linear operator acting on bounded functions. The nonlinear equation with a parameter z in the complex upper half‐plane ℍ has a unique …