An Approach of Adaptive Signal Separation Based on Operator and Locally Orthogonal Constraint

Yi Xiao-lei; Peng Si-long; Luan Shi-chao

doi:10.11999/JEIT150318

Volume 37 Issue 11

Nov. 2015

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Yi Xiao-lei, Peng Si-long, Luan Shi-chao. An Approach of Adaptive Signal Separation Based on Operator and Locally Orthogonal Constraint[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2613-2620. doi: 10.11999/JEIT150318

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An Approach of Adaptive Signal Separation Based on Operator and Locally Orthogonal Constraint

doi: 10.11999/JEIT150318

1.
(Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China)
2.
(China Aero-polytechnology Establishment, Beijing 100028, China)

Funds:

The National Natural Science Foundation of China (61032007, 61201375)

Received Date: 2015-03-17
Rev Recd Date: 2015-06-12
Publish Date: 2015-11-19

Abstract

Abstract

An operator-based approach for adaptive signal separation is proposed by using the locally orthogonal constraint and adopting back projection strategy. The approach adaptively separates a signal into additive subcomponents and a residual signal, where the subcomponents are in the null space of the operators. Experiments, including simulated signals and a real-life signal, demonstrate the feasibility, efficiency, and practicability of the proposed approach for solving the mode mixing phenomenon.
- Adaptive signal separation,
- Locally orthogonal,
- Back projection strategy,
- Null space pursuit

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References(17)

References

Huang N E , Shen Z, and Long S R. A new view of nonlinear water waves: the Hilbert spectrum[J]. Annual Review of Fluid Mechanics, 1999, 31: 417-457.

Yu D J, Cheng J S, and Yang Y. Application of emd method and hilbert spectrum to the fault diagnosis of roller bearings[J]. Mechanical Systems and Signal Processing, 2005, 19(2): 259-270.

Pai P F and Palazotto A N. Hht-based nonlinear signal processing method for parametric and non-parametric identification of dynamical systems[J]. International Journal of Mechanical Sciences, 2008, 50(12): 1619-1635.

Huang N E, Shen Z, Long S R, et al.. The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis[J]. Proceedings of the Royal Society of London(series A),1998, 454(1971): 903-995.

Peng S L and Hwang W L. Adaptive signal decomposition based on local narrow band signals[J]. IEEE Transactions on Signal Processing, 2008, 56(7): 2669-2676.

Peng S L and Hwang W L. Null space pursuit: An operator-based approach to adaptive signal separation[J]. IEEE Transactions on Signal Processing, 2010, 58(5): 2475-2483.

Mallat S and Zhang Z. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12): 3397-3415.

Vese L and Osher S. Modeling textures with total variation minimization and oscillating patterns in image processing[J]. Journal of Scientific Computing, 2003, 19(3): 553-572.

Bobin J, Starck J L, Fadili J M, et al.. Morphological component analysis: an adaptive thresholding strategy[J]. IEEE Transactions on Image Processing, 2007, 16(11): 2675-2683.

Yi X L, Hu X Y, and Peng S L. An operator-based and sparsity-based approach to adaptive signal separation[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, (ICASSP), Vancouver, BC, 2013: 6186-6190.

Hu X Y, Peng S L, and Hwang W L. Multicomponent am-fm signal separation and demodulation with null space pursuit[J]. Signal, Image and Video Processing, 2013, 7(6): 1093-1102.

肖维维, 栾卫军, 彭思龙. 基于三阶线性微分算子的零空间追踪算法[J]. 系统工程理论与实践, 2013, 33(5): 1283-1288.

Xiao Wei wei, Luan Wei jun, and Peng si long. Null space pursuit based on the three order linear differentialoperator[J]. Systems EngineeringTheory Practice, 2013, 33(5): 1283-1288.

Hu X Y, Peng S L, and Hwang W L. An integral operator based adaptive signal separation approach[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, (ICASSP), Vancouver, BC, 2013: 6103-6107.

Hu X Y, Peng S L, and Hwang W L. Adaptive integral operators for signal separation[J]. Signal Processing Letters, 2015, 22(9): 1383-1387.

Wu Z H and Huang N E. Ensemble empirical mode decomposition: A noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.

Deering R and Kaiser J F. The use of a masking signal to improve empirical mode decomposition[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, (ICASSP), Philadelphia, Pennsylvania, USA, 2005: 18-23.

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