- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1661-7746
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
A linearly convergent algorithm for sparse signal reconstruction ; volume:20 ; number:4 ; day:23 ; month:10 ; year:2018 ; pages:1-13 ; date:11.2018
Journal of fixed point theory and applications ; 20, Heft 4 (23.10.2018), 1-13, 11.2018
- Creator
-
Feng, Dexiang
Wang, Xueyong
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1007/s11784-018-0635-1
- URN
-
urn:nbn:de:101:1-2019011020573162515179
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
- 14.08.2025, 10:56 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Feng, Dexiang
- Wang, Xueyong
- SpringerLink (Online service)
Other Objects (12)
Linearly convergent bilevel optimization with single-step inner methods
Linearly convergent nonoverlapping domain decomposition methods for quasilinear parabolic equations
An efficient algorithm with fast convergence rate for sparse graph signal reconstruction
The Boosted DC Algorithm for Linearly Constrained DC Programming
Convergent Data-Driven Regularizations for CT Reconstruction
Epi-convergent scenario generation method for stochastic problems via sparse grid
Atmospheric inverse modeling via sparse reconstruction
Compressed Sensing and Sparse Reconstruction Algorithms
A convergent relaxation of the Douglas–Rachford algorithm
Sparse Reconstruction and Damage Imaging Method Based on Uniform Sparse Sampling
Asymptotic equivalent analysis of the LMS algorithm under linearly filtered processes
Modeling linearly and non-linearly dependent simulation input data
Linearly convergent bilevel optimization with single-step inner methods
Linearly convergent nonoverlapping domain decomposition methods for quasilinear parabolic equations
An efficient algorithm with fast convergence rate for sparse graph signal reconstruction
The Boosted DC Algorithm for Linearly Constrained DC Programming
Convergent Data-Driven Regularizations for CT Reconstruction
Epi-convergent scenario generation method for stochastic problems via sparse grid
Atmospheric inverse modeling via sparse reconstruction
Compressed Sensing and Sparse Reconstruction Algorithms
A convergent relaxation of the Douglas–Rachford algorithm
Sparse Reconstruction and Damage Imaging Method Based on Uniform Sparse Sampling
Asymptotic equivalent analysis of the LMS algorithm under linearly filtered processes
Modeling linearly and non-linearly dependent simulation input data
Linearly convergent bilevel optimization with single-step inner methods
Linearly convergent nonoverlapping domain decomposition methods for quasilinear parabolic equations
An efficient algorithm with fast convergence rate for sparse graph signal reconstruction
The Boosted DC Algorithm for Linearly Constrained DC Programming
Convergent Data-Driven Regularizations for CT Reconstruction
Epi-convergent scenario generation method for stochastic problems via sparse grid
Atmospheric inverse modeling via sparse reconstruction
Compressed Sensing and Sparse Reconstruction Algorithms
A convergent relaxation of the Douglas–Rachford algorithm
Sparse Reconstruction and Damage Imaging Method Based on Uniform Sparse Sampling
Asymptotic equivalent analysis of the LMS algorithm under linearly filtered processes