[PDF] Top 20 Nonlinear and Stochastic Methods in Neurosciences
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Nonlinear and Stochastic Methods in Neurosciences
... OVERVIEW In this chapter we define a new class of bidimensional integrate-and-fire neuron mod- els being computationally efficient and biologically plausible, ...observed in in vivo or ... Voir le document complet
481
A Survey of Stochastic Simulation and Optimization Methods in Signal Processing
... ONCLUSIONS AND O BSERVATIONS In writing this paper we have sought to provide an intro- duction to stochastic simulation and optimization methods in a tutorial format, but which ... Voir le document complet
19
Multiscale modeling and numerical methods in nonlinear elasticity
... problem and statement of the main results For the numerical homogenization of elliptic problems, three major issues can be identified: the design of a numerical method, the convergence of the method and ... Voir le document complet
257
Comparison of interval and stochastic methods for uncertainty quantification in metal forming
... Interval and stochastic methods provide different types of insight : ◆ Interval methods describe the impact of the manufacturing variability in terms of ranges of values for properties ... Voir le document complet
20
Comparative analysis of stochastic and non-stochastic methods for the evaluation of uncertainties in simulated and experimental data
... propagation in the case of system parameters that can be treated as random variables following known probability ...imprecise in- formation, and that’s why non-stochastic approaches were ... Voir le document complet
3
A Survey of Stochastic Simulation and Optimization Methods in Signal Processing
... expectations and demands on the performance of such methods are constantly ...SP methods are now expected to deal with challenging problems that require ever more complex models, and more ... Voir le document complet
20
Asymptotic methods in stochastic control and applications in finance
... benchmark and of finite ...processes. In this chapter, we consider a reasonable class of continuous control strategies including singular ones, and give a condition under which the option payoff is ... Voir le document complet
225
Performance of nonlinear targeted energy transfer under stochastic and deterministic excitations
... Historically, the principle of Targeted Energy Transfer (TET) was initiated by the work of Gendelman et al. [?] [?]. This allows to highlight the efficiency of a NES to mitigate the impact of vibration on structures. The ... Voir le document complet
3
Stochastic gravitational wave background : detection methods in non-Gaussian regimes
... etc.), and using the assumed density to derive, subject to analytical tractability, an expression for the log likelihood, which can subsequently be used to perform parameter ...is in general impossible to ... Voir le document complet
243
Modelization and valuation methods of gas contracts: Stochastic control approaches
... D'une part, nous avons identié des contraintes non triviales intervenant dans les contrats de stockage qui sont dus aux caractéristiques opérationnelles des actifs de stockage. L'évaluation d'actifs de stockage de gaz ... Voir le document complet
227
Recent developments in spectral stochastic methods for the numerical solution of stochastic partial differential equations
... of stochastic partial dierential equations Anthony Nouy Abstract Uncertainty quantication appears today as a crucial point in numerous branches of science and ...engineering. In the last two ... Voir le document complet
59
Fully nonlinear stochastic partial differential equations: non-smooth equations and applications
... even in the deterministic case, that there are no global smooth solutions in ...fully nonlinear character of the equations seems to make them inaccessible to the classical martingale theory employed ... Voir le document complet
12
Nonlinear Perron-Frobenius theory and mean-payoff zero-sum stochastic games
... 4 In Chapter 4 , we first consider the case of games with a bounded payment ...show in Theorem ...arise in games with no instantaneous payments, and for that reason we shall call them ... Voir le document complet
127
Stochastic numerical methods for Piecewise Deterministic Markov Processes. Applications in Neuroscience
... ones in the way we construct an approximation of our original ...[21]). In the first step, using the discretised initial flow and thinning, we simulate explicitly the first jump time and the ... Voir le document complet
125
Asymptotic properties of nonlinear estimates in stochastic models with finite design space
... (x)θ, and stochastic regressors f(x i ) (Example 1 in the same paper shows that these conditions are in some sense weakest ...Here and in what follows we denote by λ min (M) ... Voir le document complet
15
Numerical methods for the bidimensional Maxwell–Bloch equations in nonlinear crystals
... propagation and short pulses, one should use the PSTD scheme as it is the fastest of the three exposed in this ...contained in the computational domain as with the pseudospectral ...material ... Voir le document complet
32
Numerical Methods and Deep Learning for Stochastic Control Problems and Partial Differential Equations
... results In this section, we propose several settings to test the efficiency of Qknn on simulated order ...0, and take the wealth of the market maker as terminal reward, ...constant in some tests, ... Voir le document complet
271
Lie-Trotter Splitting for the Nonlinear Stochastic Manakov System
... 0 and θ “ π{4, η “ ...scheme and time discretization. 5.1. Strong convergence. In this subsection we will numerically demonstrate the mean- square orders of convergence of the four numerical schemes ... Voir le document complet
35
Development of new scenario decomposition techniques for linear and nonlinear stochastic programming
... approaches in Table ...results in a cyclic behavior of PHA between two solutions, none of them satisfying the NA ...constraints. In her example, the penalty parameter oscillates between two inverse ... Voir le document complet
80
Stochastic Formal Methods for Hybrid Systems
... side and its software on the other ...Lévy’s and Markov’s inequalities and it presents a formal theory of random variables with a special focus on producing concrete ...fit in our framework ... Voir le document complet
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