An iterative algorithm for sparse and constrained recovery with applications to divergence-free current reconstructions in magneto-encephalography.
Ignace LorisCaroline VerhoevenPublished in: Comput. Optim. Appl. (2013)
Keyphrases
- learning algorithm
- computational complexity
- improved algorithm
- np hard
- computational cost
- cost function
- linear programming
- optimal solution
- preprocessing
- significant improvement
- dynamic programming
- theoretical analysis
- high quality
- recovery algorithm
- tree structure
- expectation maximization
- high accuracy
- experimental evaluation
- k means
- denoising
- optimization algorithm
- detection algorithm
- clustering method
- image restoration
- matching algorithm
- iterative process
- objective function