Results 31 to 40 of about 987 (182)
Ensemble Kalman filter in latent space using a variational autoencoder pair
The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans +4 more
wiley +1 more source
Optimal Homogeneous ℒp$$ {\boldsymbol{\mathcal{L}}}_{\boldsymbol{p}} $$‐Gain Controller
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
On a Lebesgue constant of interpolation rational process at the Chebyshev – Markov nodes
In the present paper estimate of a Lebesgue constant of the interpolation rational Lagrange process on the segment [−1 ,1] at the Chebyshev – Markov cosine fractions nodes is considered.
Yauheni A. Rouba +2 more
doaj
Optimal Gain Selection for the Arbitrary‐Order Homogeneous Differentiator
ABSTRACT Differentiation of noisy signals is a relevant and challenging task. Widespread approaches are the linear high‐gain observer acting as a differentiator and Levant's robust exact differentiator with a discontinuous right‐hand side. We consider the family of arbitrary‐order homogeneous differentiators, which includes these special cases.
Benjamin Calmbach +2 more
wiley +1 more source
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
Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms
Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim +2 more
wiley +1 more source
Potential Operators in Variable Exponent Lebesgue Spaces: Two-Weight Estimates
Two-weighted norm estimates with general weights for Hardy-type transforms and potentials in variable exponent Lebesgue spaces defined on quasimetric measure spaces are established.
Sarwar Muhammad +2 more
doaj
BABENKO'S WORK ON SPHERICAL LEBESGUE CONSTANTS
Summary: The idea of this note is two-fold. On the one hand, this is a preface to the publication of English translation of the celebrated K. I. Babenko' preprint. On the other hand, we give a brief background of the topic at that time and in the subsequent years.
openaire +2 more sources
Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies
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
Schur's lemma and best constants in weighted norm inequalities
Strong forms of Schur's Lemma and its converse are proved for maps taking non-negative functions to non-negative functions and having formal adjoints.
Gord Sinnamon
doaj

