Results 61 to 70 of about 8,171,715 (369)
Universality of Random Matrix Dynamics [PDF]
Acta Physica Polonica B, 2020 15 pages, 3 ...
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Randomness of random networks: A random matrix analysis [PDF]
EPL (Europhysics Letters), 2009 We analyze complex networks under random matrix theory framework. Particularly, we show that $ _3$ statistic, which gives information about the long range correlations among eigenvalues, provides a qualitative measure of randomness in networks. As networks deviate from the regular structure, $ _3$ follows random matrix prediction of linear behavior ...
Jalan, S., Bandyopadhyay, J.N.
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Sensors, 2014 Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects.
Borui Li +3 more
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Pseudo-hermitian random matrix models: General formalism
Nuclear Physics B, 2022 Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite dimensional ...
Joshua Feinberg, Roman Riser
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Zhongguo dianli, 2020 Reactive power optimization and voltage management of distribution networks is very important for the optimal operation of distribution networks. By introducing big data theory into reactive power optimization of distribution networks, a reactive power ...
Ran AN +6 more
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Unbalanced multi-drawing urn with random addition matrix [PDF]
Arab Journal of Mathematical Sciences, 2020 In this paper, we consider a two color multi-drawing urn model. At each discrete time step, we draw uniformly at random a sample of m balls (m≥1) and note their color, they will be returned to the urn together with a random number of balls depending on ...
Aguech Rafik, Selmi Olfa
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International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Massive MIMO as a Big Data System: Random Matrix Models and Testbed
IEEE Access, 2015 This paper has two parts. The first one deals with how to use large random matrices as building blocks to model the massive data arising from the massive (or large-scale) multiple-input, multiple-output (MIMO) system. As a result, we apply this model for
Changchun Zhang, Robert C. Qiu
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Quaternions, números complexos e os ensembles de matrizes aleatórias
Revista Brasileira de Ensino de FísicaNeste trabalho dois ensembles de matrizes aleatórias são construídos com detalhes refinados. São eles: o Ensemble Gaussiano Unitário cujos elementos das matrizes são números complexos e o Ensemble Gaussiano Simplético, cujos elementos das matrizes são ...
A.C Bertuola
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