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Statistical modelling of higher-order correlations in pools of neural activity
(Elsevier Science, 2013-03)
Simultaneous recordings from multiple neural units allow us to investigate the activity of very large neural ensembles. To understand how large ensembles of neurons process sensory information, it is necessary to develop ...
The Fourth-order Dispersive Nonlinear Schrodinger Equation: Orbital Stability Of A Standing Wave
(SIAM PUBLICATIONSPHILADELPHIA, 2015)
Radiative corrections to Lorentz-invariance violation with higher-order operators: Fine-tuning problem revisited
(2014)
We study the possible effects of large Lorentz violations that can appear in the effective models in which the
Lorentz symmetry breakdown is performed with higher-order operators. For this we consider the Myers and ...
Higher-order cumulants drive neuronal activity patterns, inducing UP-DOWN states in neural populations
(Molecular Diversity Preservation International, 2020-04)
A major challenge in neuroscience is to understand the role of the higher-order correlations structure of neuronal populations. The dichotomized Gaussian model (DG) generates spike trains by means of thresholding a ...
Perturbative unitarity and higher-order Lorentz symmetry breaking
(2018)
We study perturbative unitarity in the scalar sector of the Myers-Pospelov model. The model introduces a preferred four-vector n which breaks Lorentz symmetry and couples to a five-dimension operator. When the preferred ...
Higher-order asymptotic refinements for score tests in proper dispersion models
(2001)
This paper develops second-order asymptotic theory for score tests in proper dispersion models without imposing known dispersion. Our results can be used to provide an Edgeworth expansion for the test statistic or to obtain ...
VOICE ACTIVITY DETECTION BASED ON HIGHER ORDER CUMULANTS AND CONVOLUTIONVOICE ACTIVITY DETECTION BASED ON HIGHER ORDER CUMULANTS AND CONVOLUTION
(Departamento de Matemática Aplicada. Facultad de Matemática y Computación. Universidad de La Habana, 2023)
Higher-Order Partial Least Squares (HOPLS) : a generalized multi-linear regression method
(IEEE Computer Society, 2013-07)
A new generalized multilinear regression model, termed the Higher-Order Partial Least Squares (HOPLS), is introduced with the aim to predict a tensor (multiway array) Y from a tensor X through projecting the data onto the ...