A comparative study of multi-objective optimization algorithms for sparse signal reconstruction

The development of the efficient sparse signal recovery algorithm is one of the important problems of the compressive sensing theory. There exist many types of sparse signal recovery methods in compressive sensing theory. These algorithms are classified into several categories like convex optimizati...

Full description

Saved in:

Bibliographic Details
Published in:	The Artificial intelligence review Vol. 55; no. 4; pp. 3153 - 3181
Main Authors:	Erkoc, Murat Emre, Karaboga, Nurhan
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.04.2022 Springer Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Comparative analysis Comparative studies Computational geometry Computer Science Convex analysis Convexity Intelligence Knee Mathematical optimization Multiple objective analysis Objectives Optimization Optimization algorithms Optimization techniques Recovery Search methods Signal reconstruction Theory Multi-objective optimization Knee region Sparse reconstruction Evolutionary algorithm Local search method Compressed sensing
ISSN:	0269-2821, 1573-7462
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!