Results 41 to 50 of about 4,913 (124)
Sobolev embeddings in grand variable Herz-Morrey Besov spaces
Boundary Value ProblemsThis paper develops a comprehensive framework for the study of grand variable Herz-Morrey Besov spaces with variable smoothness and integrability.
Babar Sultan, Amjad Hussain
doaj +1 more source
Optimal Homogeneous ℒp$$ {\boldsymbol{\mathcal{L}}}_{\boldsymbol{p}} $$‐Gain Controller
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Nonlinear ℋ∞$$ {\mathscr{H}}_{\infty } $$‐controllers are designed for arbitrarily weighted, continuous homogeneous systems with a focus on systems affine in the control input. Based on the homogeneous ℒp$$ {\mathcal{L}}_p $$‐norm, the input–output behavior is quantified in terms of the homogeneous ℒp$$ {\mathcal{L}}_p $$‐gain as a ...
Daipeng Zhang +3 more
wiley +1 more source
Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies
International Economic Review, EarlyView.ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi +2 more
wiley +1 more source
Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
wiley +1 more source
Likelihood Estimation for Stochastic Differential Equations with Mixed Effects
Scandinavian Journal of Statistics, EarlyView.ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios +2 more
wiley +1 more source
Fundamental function for Grand Lebesgue Spaces
, 2015 We investigate in this short article the fundamental function for the so-called Grand Lebesgue Spaces (GLS) and show in particular a one-to-one and mutually continuous accordance between its fundamental and generating function.
Ostrovsky, E., Sirota, L.
openaire +2 more sources
A Novel Mixed‐Hybrid, Higher‐Order Accurate Formulation for Kirchhoff–Love Shells
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT This paper presents a novel mixed‐hybrid finite element formulation for Kirchhoff–Love shells, designed to enable the use of standard C0$C^0$‐continuous higher‐order Lagrange elements. This is possible by introducing the components of the moment tensor as a primary unknown alongside the displacement vector, circumventing the need for C1$C^1 ...
Jonas Neumeyer, Thomas‐Peter Fries
wiley +1 more source
On MAP Estimates and Source Conditions for Drift Identification in SDEs
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck +3 more
wiley +1 more source
International Journal of Robust and Nonlinear Control, Volume 36, Issue 9, Page 4957-4970, June 2026.ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf +2 more
wiley +1 more source
Efficient Deconvolution in Populational Inverse Problems
International Journal for Numerical Methods in Engineering, Volume 127, Issue 9, 15 May 2026.ABSTRACT This work is focused on the inversion task of inferring the distribution over parameters of interest, leading to multiple sets of observations. The potential to solve such distributional inversion problems is driven by the increasing availability of data, but a major roadblock is blind deconvolution, arising when the observational noise ...
Arnaud Vadeboncoeur +2 more
wiley +1 more source