Results 141 to 150 of about 1,669,292 (291)

Self‐Healing Hydrogel‐Enabled Modular Assembly of Bilayered Skin Construct for Hair Follicle Regeneration

open access: yesAdvanced Healthcare Materials, EarlyView.
Self‐healing assembly of two cell‐laden hydrogel layers creates a biomimetic skin construct that restores both dermal and epidermal functions, resulting in accelerated wound healing and enhanced hair follicle regeneration in a full‐thickness skin wound model. ABSTRACT Alopecia remains a pervasive clinical challenge, largely owing to the limited ability
JaeWook Park   +5 more
wiley   +1 more source

Eigenmatrix for unstructured sparse recovery

open access: yesApplied and Computational Harmonic Analysis
This note considers the unstructured sparse recovery problems in a general form. Examples include rational approximation, spectral function estimation, Fourier inversion, Laplace inversion, and sparse deconvolution. The main challenges are the noise in the sample values and the unstructured nature of the sample locations.
openaire   +4 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

open access: yesAdvanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj   +8 more
wiley   +1 more source

Tensor-Based Match Pursuit Algorithm for MIMO Radar Imaging [PDF]

open access: yesRadioengineering, 2018
In MIMO radar, existing sparse imaging algorithms commonly vectorize the receiving data, which will destroy the multi-dimension structure of signal and cause the algorithm performance decline.
P. Huang, X. Li, H. Wang
doaj  

Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems. [PDF]

open access: yesIEEE Trans Inf Theory, 2020
Bernstein B   +3 more
europepmc   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

open access: yesAdvanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair   +3 more
wiley   +1 more source

Sparse Signal Recovery via Rescaled Matching Pursuit

open access: yesAxioms
We propose the Rescaled Matching Pursuit (RMP) algorithm to recover sparse signals in high-dimensional Euclidean spaces. The RMP algorithm has less computational complexity than other greedy-type algorithms, such as Orthogonal Matching Pursuit (OMP).
Wan Li, Peixin Ye
doaj   +1 more source

Sparse matrices for weighted sparse recovery

open access: yes, 2016
We derived the first sparse recovery guarantees for weighted $\ell_1$ minimization with sparse random matrices and the class of weighted sparse signals, using a weighted versions of the null space property to derive these guarantees. These sparse matrices from expender graphs can be applied very fast and have other better computational complexities ...
openaire   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena   +3 more
wiley   +1 more source

Quadratically fast IRLS for sparse signal recovery [PDF]

open access: yes, 2015
We present a new class of iterative algorithms for sparse recovery problems that combine iterative support detection and estimation. More precisely, these methods use a two state Gaussian scale mixture as a proxy for the signal model and can be ...
Ravazzi, Chiara, Magli, Enrico
core  

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