Sparse \(\ell_ {1}\) regularisation of matrix valued models for acoustic source characterisation
DOI10.1007/s11081-017-9357-2zbMath1393.94569arXiv1607.00171OpenAlexW2962728364MaRDI QIDQ724334
Michael Breuß, Gert Herold, Ennes Sarradj, Laurent Hoeltgen
Publication date: 25 July 2018
Published in: Optimization and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1607.00171
sparse recoverysplit Bregmanconvex optimisationmatrix differentiationmicrophone arrayacoustic source characterisation
Numerical optimization and variational techniques (65K10) Detection theory in information and communication theory (94A13) Hydro- and aero-acoustics (76Q05)
Related Items (5)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Estimating the Number of Clusters in a Data Set Via the Gap Statistic
- Nonlinear total variation based noise removal algorithms
- Primal and dual Bregman methods with application to optical nanoscopy
- Operator splittings, Bregman methods and frame shrinkage in image processing
- An alternating direction algorithm for matrix completion with nonnegative factors
- Error estimation for Bregman iterations and inverse scale space methods in image restoration
- Fast linearized Bregman iteration for compressive sensing and sparse denoising
- Scale space and variational methods in computer vision. Second international conference, SSVM 2009, Voss, Norway, June 1--5, 2009. Proceedings
- Tensor products and matrix differential calculus
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Error forgetting of Bregman iteration
- Nonlinear inverse scale space methods
- Optimal Parameter Selection for the Alternating Direction Method of Multipliers (ADMM): Quadratic Problems
- Linearized Bregman iterations for compressed sensing
- The Split Bregman Method for L1-Regularized Problems
- Split Bregman Methods and Frame Based Image Restoration
- Bregmanized Nonlocal Regularization for Deconvolution and Sparse Reconstruction
- Fast Alternating Direction Optimization Methods
- Projected Gradient Methods for Nonnegative Matrix Factorization
- Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
- Proximité et dualité dans un espace hilbertien
- An Iterative Regularization Method for Total Variation-Based Image Restoration
This page was built for publication: Sparse \(\ell_ {1}\) regularisation of matrix valued models for acoustic source characterisation