Results 31 to 40 of about 3,278,211 (362)
A Liouville-Type Theorem for an Elliptic Equation with Superquadratic Growth in the Gradient
Advanced Nonlinear Studies, 2020 We consider the elliptic equation -Δu=uq|∇u|p{-\Delta u=u^{q}|\nabla u|^{p}} in ℝn{\mathbb{R}^{n}} for any p>2{p>2} and q>0{q>0}. We prove a Liouville-type theorem, which asserts that any positive bounded solution is constant.
Filippucci Roberta +2 more
doaj +1 more source
AMBER/VLTI observations of the B[e] star MWC 300 [PDF]
, 2012 Aims. We study the enigmatic B[e] star MWC 300 to investigate its disk and binary with milli-arcsecond-scale angular resolution. Methods. We observed MWC 300 with the VLTI/AMBER instrument in the H and K bands and compared these observations with ...
Chelli, A. +10 more
core +4 more sources
An isogeometric analysis approach to gradient‐dependent plasticity [PDF]
International Journal for Numerical Methods in Engineering, 2017 SummaryGradient‐dependent plasticity can be used to achieve mesh‐objective results upon loss of well‐posedness of the initial/boundary value problem because of the introduction of strain softening, non‐associated flow, and geometric nonlinearity.
Kolo, I., de Borst, R.
openaire +2 more sources
Nonlinear Elliptic Inclusions with Unilateral Constraint and Dependence on the Gradient [PDF]
, 2018 We consider a nonlinear Neumann elliptic inclusion with a source (reaction term) consisting of a convex subdifferential plus a multivalued term depending on the gradient.
Nikolaos S. Papageorgiou +2 more
semanticscholar +1 more source
Pressure-dependence of the aortic valve gradient
Journal of the American College of Cardiology, 1998 Dipendenza lineare el gradiente transaortico dalla pressione sistolica aortica e dalle resistenze ...
LEONI, LOIRA +6 more
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Training Neural Networks by Time-Fractional Gradient Descent
Axioms, 2022 Motivated by the weighted averaging method for training neural networks, we study the time-fractional gradient descent (TFGD) method based on the time-fractional gradient flow and explore the influence of memory dependence on neural network training. The
Jingyi Xie, Sirui Li
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Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains [PDF]
, 2018 We consider the minimization of an objective function given access to unbiased estimates of its gradient through stochastic gradient descent (SGD) with constant step-size. While the detailed analysis was only performed for quadratic functions, we provide
Bach, Francis +2 more
core +3 more sources
The temperature dependence of gradient system response characteristics [PDF]
Magnetic Resonance in Medicine, 2019 PurposeThe gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non‐Cartesian k‐space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF.MethodsGSTF self‐ and B0‐cross‐terms were acquired for a 3T Siemens ...
Manuel Stich +7 more
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Impurity transport in temperature gradient driven turbulence [PDF]
, 2011 In the present paper the transport of impurities driven by trapped electron (TE) mode turbulence is studied. Non-linear (NL) gyrokinetic simulations using the code GENE are compared with results from quasilinear (QL) gyrokinetic simulations and a ...
A. Skyman +3 more
core +2 more sources
Quasilinear equations with dependence on the gradient
Nonlinear Analysis: Theory, Methods & Applications, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
De Figueiredo, Djairo G. +2 more
openaire +3 more sources