A Sparse Decomposition Method for Periodic Signal Mixtures

Makoto NAKASHIZUKA

doi:10.1093/ietfec/e91-a.3.791

A Sparse Decomposition Method for Periodic Signal Mixtures

Makoto NAKASHIZUKA

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This study proposes a method to decompose a signal into a set of periodic signals. The proposed decomposition method imposes a penalty on the resultant periodic subsignals in order to improve the sparsity of decomposition and avoid the overestimation of periods. This penalty is defined as the weighted sum of the l₂ norms of the resultant periodic subsignals. This decomposition is approximated by an unconstrained minimization problem. In order to solve this problem, a relaxation algorithm is applied. In the experiments, decomposition results are presented to demonstrate the simultaneous detection of periods and waveforms hidden in signal mixtures.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.3 pp.791-800

Publication Date: 2008/03/01

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Online ISSN: 1745-1337

DOI: 10.1093/ietfec/e91-a.3.791

Type of Manuscript: PAPER

Category: Digital Signal Processing

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Makoto NAKASHIZUKA, "A Sparse Decomposition Method for Periodic Signal Mixtures" in IEICE TRANSACTIONS on Fundamentals, vol. E91-A, no. 3, pp. 791-800, March 2008, doi: 10.1093/ietfec/e91-a.3.791.
Abstract: This study proposes a method to decompose a signal into a set of periodic signals. The proposed decomposition method imposes a penalty on the resultant periodic subsignals in order to improve the sparsity of decomposition and avoid the overestimation of periods. This penalty is defined as the weighted sum of the l₂ norms of the resultant periodic subsignals. This decomposition is approximated by an unconstrained minimization problem. In order to solve this problem, a relaxation algorithm is applied. In the experiments, decomposition results are presented to demonstrate the simultaneous detection of periods and waveforms hidden in signal mixtures.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.3.791/_p

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@ARTICLE{e91-a_3_791,
author={Makoto NAKASHIZUKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Sparse Decomposition Method for Periodic Signal Mixtures},
year={2008},
volume={E91-A},
number={3},
pages={791-800},
abstract={This study proposes a method to decompose a signal into a set of periodic signals. The proposed decomposition method imposes a penalty on the resultant periodic subsignals in order to improve the sparsity of decomposition and avoid the overestimation of periods. This penalty is defined as the weighted sum of the l₂ norms of the resultant periodic subsignals. This decomposition is approximated by an unconstrained minimization problem. In order to solve this problem, a relaxation algorithm is applied. In the experiments, decomposition results are presented to demonstrate the simultaneous detection of periods and waveforms hidden in signal mixtures.},
keywords={},
doi={10.1093/ietfec/e91-a.3.791},
ISSN={1745-1337},
month={March},}

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TY - JOUR
TI - A Sparse Decomposition Method for Periodic Signal Mixtures
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 791
EP - 800
AU - Makoto NAKASHIZUKA
PY - 2008
DO - 10.1093/ietfec/e91-a.3.791
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2008
AB - This study proposes a method to decompose a signal into a set of periodic signals. The proposed decomposition method imposes a penalty on the resultant periodic subsignals in order to improve the sparsity of decomposition and avoid the overestimation of periods. This penalty is defined as the weighted sum of the l₂ norms of the resultant periodic subsignals. This decomposition is approximated by an unconstrained minimization problem. In order to solve this problem, a relaxation algorithm is applied. In the experiments, decomposition results are presented to demonstrate the simultaneous detection of periods and waveforms hidden in signal mixtures.
ER -