Results 121 to 130 of about 332,141 (275)
A state observer-based robust control method for perturbation-containing nonlinear discrete interconnected Systems. [PDF]
Sun Y, Wen Y, Li H, Du Y.
europepmc +1 more source
This work presents a dispersive full‐channel Jones matrix modulation strategy using single‐layer metasurface. By synergizing wavelength dispersion engineering with elliptical polarization bases, independent control of four Jones matrix channels is achieved across multiple wavelengths.
Hairong He +10 more
wiley +1 more source
Automated diagnosis of pulmonary nodules in 3D PET/CT images using dual-path densely connected networks with cross-modal fusion. [PDF]
Liao F +6 more
europepmc +1 more source
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
wiley +1 more source
Numerical simulation of a nonlinear hepatitis B virus mathematical model using the Dickson collocation technique. [PDF]
El-Shenawy A, El-Gamel M, Abouelsaid M.
europepmc +1 more source
A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu +9 more
wiley +1 more source
Exploring novel semi-inner product reproducing Kernels in Banach space for robust Kernel methods. [PDF]
Ding Y, Zhao Y, Pei Y.
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source

