Results 101 to 110 of about 17,823 (205)

Genus expansion for real Wishart matrices

, 2009
We present an exact formula for moments and cumulants of several real compound Wishart matrices in terms of an Euler characteristic expansion, similar to the genus expansion for complex random matrices.
A. Guionnet, A. Hatcher, A. Zvonkin, C. Emily I. Redelmeier, G.W. Anderson, I.P. Goulden, J. Wishart, J.A. Mingo, J.S. Rosenthal, M. Capitaine, M. Capitaine, M. Henle, M. Mulase, M. Mulase, N.M. Ercolani, P. Billingsley, P. Graczyk, P.J. Hanlon, S. Janson, S.K. Lando, W. Bryc, W.T. Tutte   +21 more
core   +1 more source

Semiclassical noise beyond the second cumulant

, 2006
We show how the semiclassical Langevin method can be extended to calculations of higher-than-second cumulants of noise. These cumulants are affected by indirect correlations between the fluctuations, which may be considered as "noise of noise." We ...
Nagaev, Kirill E.
core   +1 more source

Statistics of Heat Transfer in Mesoscopic Circuits

, 2003
A method to calculate the statistics of energy exchange between quantum systems is presented. The generating function of this statistics is expressed through a Keldysh path integral.
A.A.M. Staring, A.S. Dzurak, B. Reulet, C.W.J. Beenakker, C.W.J. Beenakker, J. Eom, J.P. Kauppinen, J.P. Pekola, K. Schwab, L.S. Levitov, L.S. Levitov, Luis G.C. Rego, M. Fleischhauer, M. Kindermann, M. Kindermann, M. Kindermann, M. Kindermann, M. Rokni, P. Kim, S. Pilgram, S. Pilgram, S. Pilgram, U. Sivan, W. Belzig, W. Belzig, Y. Adamov, Y. Adamov, Ya.M. Blanter, Ya.M. Blanter, Yu.V. Nazarov   +29 more
core   +2 more sources

Feedback through graph motifs relates structure and function in complex networks

, 2018
In physics, biology and engineering, network systems abound. How does the connectivity of a network system combine with the behavior of its individual components to determine its collective function?
Brunton, Steven L., Cain, Nicholas, Hu, Yu, Kutz, J. Nathan, Mihalas, Stefan, Shea-Brown, Eric   +5 more
core   +1 more source

A centrality-independent framework for revealing genuine higher-order cumulants in heavy-Ion collisions

Physics Letters B
We propose a novel centrality definition-independent method for analyzing higher-order cumulants, specifically addressing the challenge of volume fluctuations that dominate in low-energy heavy-ion collisions.
Zhaohui Wang, Xiaofeng Luo
doaj   +1 more source

Sliding window higher-order cumulants for detection of eye blink artifact from short segments of single-channel EEG [PDF]

PeerJ Computer Science
Background The prevalence of single-channel electroencephalogram (EEG) is increasing. However, eye blink artifacts can contaminate EEG signals, potentially impacting their clinical utility.
Guojing Wang, Hongyun Liu, Shijing Wu, Xiaohua Yu, Buqing Wang, Weidong Wang   +5 more
doaj   +2 more sources

Nonlinear System Identification with a Real–Coded Genetic Algorithm (RCGA)

International Journal of Applied Mathematics and Computer Science, 2015
This paper is devoted to the blind identification problem of a special class of nonlinear systems, namely, Volterra models, using a real-coded genetic algorithm (RCGA).
Cherif Imen, Fnaiech Farhat
doaj   +1 more source

UAV Signal Modulation Recognition Algorithm Based on Joint Features

IEEE Access
The precise identification of drone modulation schemes serves as a fundamental basis for achieving intelligent drone recognition. To address the limitations of existing algorithms that overly rely on single features, resulting in low recognition rates ...
Yang Zheng, Zhihai Zhuo
doaj   +1 more source

Higher-order spin noise statistics

New Journal of Physics, 2013
The optical spin noise spectroscopy (SNS) is a minimally invasive route toward obtaining dynamical information about electrons and atomic gases by measuring mesoscopic time-dependent spin fluctuations. Recent improvements of the sensitivity of SNS should
Fuxiang Li, Avadh Saxena, Darryl Smith, Nikolai A Sinitsyn   +3 more
doaj   +1 more source

Separation Of Sources Using Higher-Order Cumulants

SPIE Proceedings, 1989
The problem is to recover stochastic processes from an unknown stationary linear transform. Our contribution is two-fold. First we focus on instantaneous mixtures: observation e(t) is assumed to write as a regular linear transform of the sources, x(t), as e(t)=B_0x(t).
openaire   +2 more sources