TY - GEN
T1 - A gridless sparse method for super-resolution of harmonics
AU - Yang, Zai
N1 - Publisher Copyright:
© EURASIP 2017.
PY - 2017/10/23
Y1 - 2017/10/23
N2 - As a special frequency estimation problem, harmonics estimation has applications in speech and audio processing, power systems, healthcare monitoring, etc. In this paper, we make a first attempt to propose a gridless sparse method for harmonics estimation exploiting the harmonics structure. The method uses the atomic norm with carefully designed atoms and is formulated as a convex optimization problem. Its performance is demonstrated via numerical simulations.
AB - As a special frequency estimation problem, harmonics estimation has applications in speech and audio processing, power systems, healthcare monitoring, etc. In this paper, we make a first attempt to propose a gridless sparse method for harmonics estimation exploiting the harmonics structure. The method uses the atomic norm with carefully designed atoms and is formulated as a convex optimization problem. Its performance is demonstrated via numerical simulations.
KW - Atomic norm
KW - Frequency estimation
KW - Gridless sparse method
KW - Group sparsity
KW - Harmonics estimation
UR - https://www.scopus.com/pages/publications/85034750898
U2 - 10.23919/EUSIPCO.2017.8081579
DO - 10.23919/EUSIPCO.2017.8081579
M3 - 会议稿件
AN - SCOPUS:85034750898
T3 - 25th European Signal Processing Conference, EUSIPCO 2017
SP - 2096
EP - 2100
BT - 25th European Signal Processing Conference, EUSIPCO 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th European Signal Processing Conference, EUSIPCO 2017
Y2 - 28 August 2017 through 2 September 2017
ER -