Buscar
Mostrando ítems 1-10 de 132
Gaussian ensembles distributions from mixing quantum systems
(Elsevier Science, 2017-08)
In the context of dynamical systems we present a derivation of the Gaussian ensembles distributions from quantum systems having a classical analogue that is mixing. We find that factorization property is satisfied for the ...
CHAOTIC DYNAMICS AND THE GOE-GUE TRANSITION
(Iop Publishing LtdBristolInglaterra, 1995)
Scaling Limits of Correlations of Characteristic Polynomials for the Gaussian beta-Ensemble with External Source
(2015)
We study the averaged product of characteristic polynomials of large random matrices in the Gaussian beta-ensemble perturbed by an external source of finite rank. We prove that at the edge of the spectrum, the limiting ...
Deformed Gaussian-orthogonal-ensemble description of small-world networks
(AMER PHYSICAL SOC, 2009)
The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully ...
Deformed Gaussian orthogonal ensemble and the statistical fluctuations in the spectra of the quartic oscillator
(1999-12-01)
The nearest-neighbor spacing distributions proposed by four models, namely, the Berry-Robnik, Caurier-Grammaticos-Ramani, Lenz-Haake, and the deformed Gaussian orthogonal ensemble, as well as the ansatz by Brody, are applied ...
A Maximum Likelihood Ensemble Filter via a Modified Cholesky Decomposition for Non-Gaussian Data Assimilation
(MDPI AG, 2020-02-06)
This paper proposes an efficient and practical implementation of the Maximum Likelihood Ensemble Filter via a Modified Cholesky decomposition (MLEF-MC).
Machine Learning Classifier Approach with Gaussian Process, Ensemble boosted Trees, SVM, and Linear Regression for 5G Signal Coverage Mapping
This article offers a thorough analysis of the machine learning classifiers approaches for the collected Received Signal Strength Indicator (RSSI) samples which can be applied in predicting propagation loss, used for network ...