TY - JOUR
T1 - Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction
AU - Wu, Caiying
AU - Wang, Jing
AU - Alcantara, Jan Harold
AU - Chen, Jein Shan
N1 - Funding Information:
Caiying Wu and Jing Wang are supported by the Natural Science Foundation of Inner Mongolia Autonomous Region (2018MS01016). Jan Harold Alcantara and Jein-Shan Chen are supported by the Ministry of Science and Technology, Taiwan.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - In this paper, we propose a new smoothing strategy along with conjugate gradient algorithm for the signal reconstruction problem. Theoretically, the proposed conjugate gradient algorithm along with the smoothing functions for the absolute value function is shown to possess some nice properties which guarantee global convergence. Numerical experiments and comparisons suggest that the proposed algorithm is an efficient approach for sparse recovery. Moreover, we demonstrate that the approach has some advantages over some existing solvers for the signal reconstruction problem.
AB - In this paper, we propose a new smoothing strategy along with conjugate gradient algorithm for the signal reconstruction problem. Theoretically, the proposed conjugate gradient algorithm along with the smoothing functions for the absolute value function is shown to possess some nice properties which guarantee global convergence. Numerical experiments and comparisons suggest that the proposed algorithm is an efficient approach for sparse recovery. Moreover, we demonstrate that the approach has some advantages over some existing solvers for the signal reconstruction problem.
KW - Conjugate gradient algorithm
KW - l-norm regularization
KW - Signal recovery
KW - Sparse solution
UR - http://www.scopus.com/inward/record.url?scp=85102059456&partnerID=8YFLogxK
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U2 - 10.1007/s10915-021-01440-z
DO - 10.1007/s10915-021-01440-z
M3 - Article
AN - SCOPUS:85102059456
SN - 0885-7474
VL - 87
JO - Journal of Scientific Computing
JF - Journal of Scientific Computing
IS - 1
M1 - 21
ER -