Results 51 to 60 of about 11,051,325 (215)

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Comparing parameter choice methods for regularization of ill-posed problems [PDF]

, 2011
In the literature on regularization, many different parameter choice methods have been proposed in both deterministic and stochastic settings. However, based on the available information, it is not always easy to know how well a particular method will ...
Bauer, F., Lukas, M.A.
core  

Nanocrystalline LCO/LLZO Composite Cathode Films for Solid State Batteries

Advanced Energy Materials, EarlyView.
A single precursor solution is solution‐deposited and calcined at only 750°C to yield a dense, nanograined LiCoO2/LLZO composite cathode, in which both phases crystallize independently with minimal interdiffusion. Assembled into all‐solid‐state Li‐metal batteries, the composite delivers 111.7 mAh g−1 initial discharge capacity and retains 93% after 100
Lucie Quincke, Steffen Weinmann, Jesse J. Hinricher, Matteo Galasso, Chiara Althammer, Fran Kurnia, Kun Joong Kim, Wolff‐Ragnar Kiebach, Jennifer L. M. Rupp   +8 more
wiley   +1 more source

A parameter choice for Tikhonov regularization for solving nonlinear inverse problems leading to optimal convergence rates [PDF]

, 1993
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter in Tikhonov regularization for solving nonlinear ill-posed problems, which leads to optimal convergence rates.
Scherzer, Otmar
core   +1 more source

MATHEMATICAL MODELLING OF THE MAGNETIC SYSTEM BY A.N. TIKHONOV REGULARIZATION METHOD [PDF]

Chronos, 2011
A nonlinear magnetostatic inverse problem is investigated for a case when it is needed to create a required magnetic field using conductors which coordinates vary on condition that current value is equal in all the conductors. It is known that the same problems fall under the category of noncorrect problems.
R. V. Polyakova, I. P. Yudin
openaire   +2 more sources

Linking community structure and climate vulnerability in desert plant assemblages of southern California

American Journal of Botany, EarlyView.
Abstract Premise Desert plant assemblages in southern California provide an opportunity to link patterns of community structure with climate‐driven vulnerability in a rapidly changing environment. California sustains an exceptionally diverse flora of approximately 4300 plant species, with 31% identified as endemic.
Hector Zumbado‐Ulate, Luis E. Barrios, Danelle A. Baronia, G. Darrel Jenerette, Lynn C. Sweet   +4 more
wiley   +1 more source

Asymptotic behaviour of the minimum bound method for choosing the regularization parameter [PDF]

, 1998
We consider a parameter choice method (called the minimum bound method) for regularization of linear ill-posed problems that was developed by Raus and Gfrerer for the case with continuous, deterministic data.
Lukas, M.A.
core  

Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems [PDF]

, 2019
We study a non-linear statistical inverse learning problem, where we observe the noisy image of a quantity through a non-linear operator at some random design points.
Mathé, Peter, Blanchard, Gilles, Rastogi, Abhishake   +2 more
core   +1 more source

Performance improvement of discrete‐time linear‐quadratic regulators applied to uncertain linear systems using the Tikhonov regularization method

Asian Journal of Control, EarlyView.
Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley   +1 more source

Prop-cut: A mesh cutting method based on Tikhonov regularization [PDF]

2009 11th IEEE International Conference on Computer-Aided Design and Computer Graphics, 2009
We present an interactive mesh cutting method in this paper, which is based on a formulation of semi-supervised learning. Users first assign foreground and background seed faces on a given triangular mesh by sketch lines. Then the system computes a scalar field across the mesh.
Hongxin Zhang 0001, Juan Wang
openaire   +1 more source