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[PDF] Top 20 Nonlinear analysis methods in neural field models

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Nonlinear analysis methods in neural field models

Nonlinear analysis methods in neural field models

... an in-depth analysis of the values of delays and connectivity properties giving rise to oscillatory behavior has yet to be ...the nonlinear stability has been studied in two papers [ Roxin ... Voir le document complet

361

Multiscale modeling and numerical methods in nonlinear elasticity

Multiscale modeling and numerical methods in nonlinear elasticity

... mathematical analysis of numerical methods for the homogenization of multiple integrals widely used in nonlinear ...These methods couple, at the mesoscopic scale, a heterogeneous ... Voir le document complet

257

Linear and nonlinear solvers for variational phase-field models of brittle fracture

Linear and nonlinear solvers for variational phase-field models of brittle fracture

... convergence in the case where A is symmetric and positive-definite. For nonlinear SOR, Ortega and Rheinboldt [ 46 , Theorem ...solution. Nonlinear Gauss-Seidel methods ( ω = 1 ) can also be ... Voir le document complet

23

New results for delayed neural field equations

New results for delayed neural field equations

... Abstract Neural field models with delays define a useful framework for modeling macroscopic parts of the cortex involving sev- eral populations of ...neurons. Nonlinear delayed integro- ... Voir le document complet

7

Stochastic neural field equations: A rigorous footing

Stochastic neural field equations: A rigorous footing

... footing in the study of epileptic-like seizures in [ 24 ...discrete models, one typically arrives at a nonlinear integro-differential equation, in which the integral term can be seen as ... Voir le document complet

41

Adaptive rational spectral methods for the linear stability analysis of nonlinear fourth-order problems

Adaptive rational spectral methods for the linear stability analysis of nonlinear fourth-order problems

... patterns in immiscible flow [38, 79, 65, ...mixtures in porous media will emerge in the next few years, and most likely the mathematical structure of these new mod- els will resemble that of ... Voir le document complet

39

The analysis of vehicle’s in-flight behaviour using quasi-LPV and nonlinear models

The analysis of vehicle’s in-flight behaviour using quasi-LPV and nonlinear models

... of in-flight behaviour are fundamental in the development of modern weaponry: they predict a projectile’s trajectory—allowing to fulfill the safety requirements for free-flight experiments—and thus aid the ... Voir le document complet

13

Fully nonlinear long-waves models in presence of vorticity

Fully nonlinear long-waves models in presence of vorticity

... weakly nonlinear. In Kim, Lynett & Socolofsky (2009), a small horizontal vorticity was also allowed in a Boussinesq type model by resorting to a simplified description for the vorticity ... Voir le document complet

33

Neural Methods for Event Extraction

Neural Methods for Event Extraction

... problem in processing this amount of data is the fact that most of them are initially unstructured, ...written in a human- understandable ...terms in a text that are relevant to a specific ...put ... Voir le document complet

153

Persistent neural states: stationary localized activity patterns in nonlinear continuous $n$-population, $q$-dimensional neural networks

Persistent neural states: stationary localized activity patterns in nonlinear continuous $n$-population, $q$-dimensional neural networks

... Abstract: Neural continuum networks are an important aspect of the modeling of macroscopic parts of the ...activity-based. In both cases our networks contain an arbitrary number, n, of interacting neuron ... Voir le document complet

41

Methods for sensitivity analysis and backward propagation of uncertainty applied on mathematical models in engineering applications

Methods for sensitivity analysis and backward propagation of uncertainty applied on mathematical models in engineering applications

... uncertainty. In addition, it consists of two main ...a nonlinear least square problem whose residues are defined using the formula that expresses the variance of the output in terms of the ... Voir le document complet

157

On Computer-Intensive Simulation and Estimation Methods for Rare Event Analysis in Epidemic Models

On Computer-Intensive Simulation and Estimation Methods for Rare Event Analysis in Epidemic Models

... statistical analysis of the spread of communicable infectious diseases have never ceased to receive attention in the applied probability and statistics ...encountered in practice (impact of ... Voir le document complet

16

Nonlinear and Stochastic Methods in Neurosciences

Nonlinear and Stochastic Methods in Neurosciences

... observed in cortical neurons. For this reason it is currently widely used, in particular for large scale simulations of neural ...of models studied in chapter 2: it emulates the ... Voir le document complet

481

Large volume multicolor nonlinear microscopy of neural tissues

Large volume multicolor nonlinear microscopy of neural tissues

... tissue in order to remove optical scatterers such as lipids and minimize refractive index ...inhomogeneities. In other terms, optical clearing techniques aim at rendering biological tissues transparent to ... Voir le document complet

182

Localized states in an unbounded neural field equation with smooth firing rate function: a multi-parameter analysis

Localized states in an unbounded neural field equation with smooth firing rate function: a multi-parameter analysis

... continuation in order to extend the study with an investigation of snaking behaviour; these methods have been applied extensively for the Swift– Hohenberg equation ( Burke and Knobloch 2006 , 2007a ; ... Voir le document complet

37

Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

... p in B Pη,PR and lower coverage rate of Q for the asymptotic method. In this study, we expected that the random effect and residual bootstrap would have good performance in NLMEM, especially ... Voir le document complet

29

Statistical Methods for Neural Network Prediction Models

Statistical Methods for Neural Network Prediction Models

... truncation. In that case, only a subset of principal components loadings is ...the field of ...reduction methods may also have effects on the generalization properties of the models ... Voir le document complet

55

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

... and Methods All animal procedures were approved by the Committee on Animal Care at the Massachusetts Institute of ...HMM-based models that have been proposed for solving other problems (14, ...currently ... Voir le document complet

7

Recurrent neural models and related problems in natural language processing

Recurrent neural models and related problems in natural language processing

... changer in this field (Manning et ...modeled in a soft way with degree of uncer- ...robust in complex NLP problems especially when non-standard expressions and errors are heavily involved ... Voir le document complet

161

Nonlinear models for neurophysiological time series

Nonlinear models for neurophysiological time series

... Fourier analysis fails to distinguish alpha rhythms from mu rhythms, which have the same peak frequency at around 10 Hz, but whose waveforms are different ( Cole and Voytek , 2017 , Hari and Puce , 2017 ...as ... Voir le document complet

145

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