Results 31 to 40 of about 418 (179)
Bilinear operator multipliers into the trace class
This paper replaces the one entitled "Modular operator multipliers into the trace". Besides the change of title, a few corrections have been made.
Le Merdy, Christian +2 more
openaire +5 more sources
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Low latency carbon budget estimates for July 2024–June 2025 combine atmospheric CO2 growth rates, fossil emissions, ocean uptake, DGVM land fluxes, and OCO‐2 inversions. The budget shows that late‐2024 land carbon losses dominate the annual anomaly, while early‐2025 recovery differs between bottom‐up models and top‐down inversions, especially in ...
Piyu Ke +32 more
wiley +1 more source
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez +10 more
wiley +1 more source
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci +6 more
wiley +1 more source
Using the wavelets characterization of inhomogeneous Lipschitz spaces, the author establishes a bilinear decomposition for products of functions in local Hardy spaces hp(X) ${h}^{p}\left(\mathcal{X}\right)$ and inhomogeneous Lipschitz spaces lip1/p−1(X)
Wang Fan
doaj +1 more source
Learning regime‐dependent governing equations: A symbolic decision tree approach
Abstract Many chemical engineering systems are governed by mechanisms that switch across operating regimes, making the data‐driven discovery of regime‐dependent governing equations essential for predictive modeling, optimization, and control. We propose symbolic decision trees for the data‐driven discovery of regime‐dependent governing equations.
Ilias Mitrai +2 more
wiley +1 more source
Minimal smoothness conditions for bilinear Fourier multipliers
The problem of finding the differentiability conditions for bilinear Fourier multipliers that are as small as possible to ensure the boundedness of the corresponding operators from products of Hardy spaces H^{p_1}\times H^{p_2} to
Miyachi, Akihiko, Tomita, Naohito
openaire +3 more sources
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
To further improve the economic benefits of operators and the low-carbon performance within the system, this paper proposes a hierarchical distributed low-carbon economic dispatch strategy for regional integrated energy systems (RIESs) based on the ...
He Jiang +3 more
doaj +1 more source

