Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor

Liu Lu; Ou Shifeng; Gao Ying

doi:doi:10.11648/j.ijiis.20190804.12

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Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor

Liu Lu, Ou Shifeng, Gao Ying

Published in International Journal of Intelligent Information Systems (Volume 8, Issue 4)

Received: 15 October 2019 Published: 18 November 2019

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Abstract

The traditional blind separation algorithm is mainly for the instantaneous mixing problem in the stable environment. In the practical applications, blind separation often takes into account the interference of the external environment, which requires that the algorithm has strong tracking performance, but the traditional algorithm can’t meet the needs. Aiming at the problem of instantaneous blind separation in non-stationary environment, constrained blind separation algorithm using variable step size and variable momentum factor is proposed in this paper. Based on the nonholonomic natural gradient algorithm, the cost function is constrained by the disturbance of the hybrid system and the constraint factors take the form of self-adaptive adjustment. According to the separation situation, the constraint factors are adjusted adaptively to accelerate the convergence speed. The variable step size based on the cost function gradient is introduced to improve the tracking performance. By incorporating momentum term, the momentum factor is adaptively adjusted to make it have better separation performance. The simulation results show that compared with the traditional algorithm, the proposed algorithm can better balance the contradiction between convergence speed and steady-state error in non-stationary environment, and has better separation performance. In the case of obvious disturbance in the mixed system, the algorithm can effectively improve the shortcomings of the traditional algorithm. In summary, constrained blind separation algorithm using variable step size and variable momentum factor proposed in this paper is effective.

Published in	International Journal of Intelligent Information Systems (Volume 8, Issue 4)
DOI	10.11648/j.ijiis.20190804.12
Page(s)	77-84
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Blind Separation, Non-stationary, Nonholonomic Natural Gradient, Adaptive, Momentum Factor

References

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[2]	S. Y. Peng, Z. H. Wang, Y. Q. Zhu, “Present Situation and Development of Blind Source Separation,” Shipboard Electronic Countermeasure, vol. 39. 2016, pp. 54-57.
[3]	W. C. Ding, H. Zhang, “Natural Gradient Blind Separation Algorithm for Optimal Search Direction,” Journal of Military communications Technology, vol. 38. 2017, pp. 12-16.
[4]	P. C. Xu, Y. H. Shen, Q. Su, “Blind source separation with variable step-size method based on a reference separation system,” IEEE International Conference on Sinal Processing, Communications and Computing, 2014, pp. 110-114.
[5]	C. Ji, K. Yang, Y. R. Wang, M. D. Liu, “Variable Step Size Nonholonomic Natural Gradient Algorithm Based on Sign Operator,” Pattern Recognition and Artificial Intelligence, vol. 27. 2014, pp. 1026-1031.
[6]	Y. L. Niu, Y. M. Wang, Y. Wang, “Improved Adaptive Algorithm of Blind Source Separation Based on Nonholonomic Natural Gradient,” Pattern Recognition and Artificial Intelligence, vol. 19. 2006, pp. 667-673.
[7]	Z. Y. Ma, T. Q. Zhang, Q. Li, X. M. Liang, “Adaptive Variable-step Blind Source Separation with Momentum Factor,” Telecommunication Engineering, vol. 59. 2019, pp. 294-300.
[8]	C. T. Li, Y. Z. Jiang, F. J. Liu, S. X. Zhang, “Step-size adaptive blind source separation algorithm with adding momentum term,” Journal of Naval University of Engineering, vol. 31. 2019, pp. 107-112.
[9]	T. Q. Zhang, B. Z. Ma, X. Z. Qiang, S. R. Quan, “Variable-step blind source separation method with adaptive momentum factor,” Journal on Communications, vol. 38. 2017, pp. 16-24.
[10]	T. Q. Zhang, B. Z. Ma, X. Z. Qiang, S. R. Quan, “Variable-step Blind Source Separation Algorithm with Adaptive Momentum Item for Chaotic Signals,” Journal of Electronics and Information Technology, vol. 39. 2017, pp. 908-914.
[11]	C. Ji, K. Yang, Y. M. Tao, X. Wang, “An adaptive variable step-size blind source separation algorithm in non-stationary environment,” Contyol and Decision, vol. 31. 2016, pp. 735-739.
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[13]	C. Ji, B. C. Tang, K. Yang, M. Sha, “Improved blind source separation based on nonholonomic natural gradient algorithm with variable step size,” 2013 China intelligent automation academic conference, 2013, pp. 761-767.
[14]	S. Amari, T. P. Chen, A. Cichocki, “Non-Holonomic Constraints in Learning Algorithms for Blind Source Separation,” Neural Computation, vol. 12. 2000, pp. 1463-1484.
[15]	Y. S. Xia, G. Feng, J. Wang, “A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints,” IEEE Trans on Neural Networks, vol. 19. 2008, pp. 1340-1353.
[16]	L. X. Yuan, W. W. Wang, J. A. Chambers. “Variable step-size sign natural gradient algorithm for sequential blind source separation,” IEEE Signal Process Letters, vol. 12. 2005, pp. 589-592.

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APA Style

Liu Lu, Ou Shifeng, Gao Ying. (2019). Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. International Journal of Intelligent Information Systems, 8(4), 77-84. https://doi.org/10.11648/j.ijiis.20190804.12

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ACS Style

Liu Lu; Ou Shifeng; Gao Ying. Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. Int. J. Intell. Inf. Syst. 2019, 8(4), 77-84. doi: 10.11648/j.ijiis.20190804.12

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AMA Style

Liu Lu, Ou Shifeng, Gao Ying. Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. Int J Intell Inf Syst. 2019;8(4):77-84. doi: 10.11648/j.ijiis.20190804.12

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@article{10.11648/j.ijiis.20190804.12,
  author = {Liu Lu and Ou Shifeng and Gao Ying},
  title = {Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor},
  journal = {International Journal of Intelligent Information Systems},
  volume = {8},
  number = {4},
  pages = {77-84},
  doi = {10.11648/j.ijiis.20190804.12},
  url = {https://doi.org/10.11648/j.ijiis.20190804.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20190804.12},
  abstract = {The traditional blind separation algorithm is mainly for the instantaneous mixing problem in the stable environment. In the practical applications, blind separation often takes into account the interference of the external environment, which requires that the algorithm has strong tracking performance, but the traditional algorithm can’t meet the needs. Aiming at the problem of instantaneous blind separation in non-stationary environment, constrained blind separation algorithm using variable step size and variable momentum factor is proposed in this paper. Based on the nonholonomic natural gradient algorithm, the cost function is constrained by the disturbance of the hybrid system and the constraint factors take the form of self-adaptive adjustment. According to the separation situation, the constraint factors are adjusted adaptively to accelerate the convergence speed. The variable step size based on the cost function gradient is introduced to improve the tracking performance. By incorporating momentum term, the momentum factor is adaptively adjusted to make it have better separation performance. The simulation results show that compared with the traditional algorithm, the proposed algorithm can better balance the contradiction between convergence speed and steady-state error in non-stationary environment, and has better separation performance. In the case of obvious disturbance in the mixed system, the algorithm can effectively improve the shortcomings of the traditional algorithm. In summary, constrained blind separation algorithm using variable step size and variable momentum factor proposed in this paper is effective.},
 year = {2019}
}

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TY  - JOUR
T1  - Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor
AU  - Liu Lu
AU  - Ou Shifeng
AU  - Gao Ying
Y1  - 2019/11/18
PY  - 2019
N1  - https://doi.org/10.11648/j.ijiis.20190804.12
DO  - 10.11648/j.ijiis.20190804.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 77
EP  - 84
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20190804.12
AB  - The traditional blind separation algorithm is mainly for the instantaneous mixing problem in the stable environment. In the practical applications, blind separation often takes into account the interference of the external environment, which requires that the algorithm has strong tracking performance, but the traditional algorithm can’t meet the needs. Aiming at the problem of instantaneous blind separation in non-stationary environment, constrained blind separation algorithm using variable step size and variable momentum factor is proposed in this paper. Based on the nonholonomic natural gradient algorithm, the cost function is constrained by the disturbance of the hybrid system and the constraint factors take the form of self-adaptive adjustment. According to the separation situation, the constraint factors are adjusted adaptively to accelerate the convergence speed. The variable step size based on the cost function gradient is introduced to improve the tracking performance. By incorporating momentum term, the momentum factor is adaptively adjusted to make it have better separation performance. The simulation results show that compared with the traditional algorithm, the proposed algorithm can better balance the contradiction between convergence speed and steady-state error in non-stationary environment, and has better separation performance. In the case of obvious disturbance in the mixed system, the algorithm can effectively improve the shortcomings of the traditional algorithm. In summary, constrained blind separation algorithm using variable step size and variable momentum factor proposed in this paper is effective.
VL  - 8
IS  - 4
ER  -

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Author Information

Liu Lu

School of Science and Technology for Opto-electronic Information, Yantai University, Yantai, China
Ou Shifeng

School of Science and Technology for Opto-electronic Information, Yantai University, Yantai, China
Gao Ying

School of Science and Technology for Opto-electronic Information, Yantai University, Yantai, China

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Plain Text BibTeX RIS

APA Style

Liu Lu, Ou Shifeng, Gao Ying. (2019). Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. International Journal of Intelligent Information Systems, 8(4), 77-84. https://doi.org/10.11648/j.ijiis.20190804.12

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ACS Style

Liu Lu; Ou Shifeng; Gao Ying. Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. Int. J. Intell. Inf. Syst. 2019, 8(4), 77-84. doi: 10.11648/j.ijiis.20190804.12

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AMA Style

Liu Lu, Ou Shifeng, Gao Ying. Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor. Int J Intell Inf Syst. 2019;8(4):77-84. doi: 10.11648/j.ijiis.20190804.12

Copy | Download

@article{10.11648/j.ijiis.20190804.12,
  author = {Liu Lu and Ou Shifeng and Gao Ying},
  title = {Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor},
  journal = {International Journal of Intelligent Information Systems},
  volume = {8},
  number = {4},
  pages = {77-84},
  doi = {10.11648/j.ijiis.20190804.12},
  url = {https://doi.org/10.11648/j.ijiis.20190804.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20190804.12},
  abstract = {The traditional blind separation algorithm is mainly for the instantaneous mixing problem in the stable environment. In the practical applications, blind separation often takes into account the interference of the external environment, which requires that the algorithm has strong tracking performance, but the traditional algorithm can’t meet the needs. Aiming at the problem of instantaneous blind separation in non-stationary environment, constrained blind separation algorithm using variable step size and variable momentum factor is proposed in this paper. Based on the nonholonomic natural gradient algorithm, the cost function is constrained by the disturbance of the hybrid system and the constraint factors take the form of self-adaptive adjustment. According to the separation situation, the constraint factors are adjusted adaptively to accelerate the convergence speed. The variable step size based on the cost function gradient is introduced to improve the tracking performance. By incorporating momentum term, the momentum factor is adaptively adjusted to make it have better separation performance. The simulation results show that compared with the traditional algorithm, the proposed algorithm can better balance the contradiction between convergence speed and steady-state error in non-stationary environment, and has better separation performance. In the case of obvious disturbance in the mixed system, the algorithm can effectively improve the shortcomings of the traditional algorithm. In summary, constrained blind separation algorithm using variable step size and variable momentum factor proposed in this paper is effective.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Constrained Blind Separation Algorithm Using Variable Step Size and Variable Momentum Factor
AU  - Liu Lu
AU  - Ou Shifeng
AU  - Gao Ying
Y1  - 2019/11/18
PY  - 2019
N1  - https://doi.org/10.11648/j.ijiis.20190804.12
DO  - 10.11648/j.ijiis.20190804.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 77
EP  - 84
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20190804.12
AB  - The traditional blind separation algorithm is mainly for the instantaneous mixing problem in the stable environment. In the practical applications, blind separation often takes into account the interference of the external environment, which requires that the algorithm has strong tracking performance, but the traditional algorithm can’t meet the needs. Aiming at the problem of instantaneous blind separation in non-stationary environment, constrained blind separation algorithm using variable step size and variable momentum factor is proposed in this paper. Based on the nonholonomic natural gradient algorithm, the cost function is constrained by the disturbance of the hybrid system and the constraint factors take the form of self-adaptive adjustment. According to the separation situation, the constraint factors are adjusted adaptively to accelerate the convergence speed. The variable step size based on the cost function gradient is introduced to improve the tracking performance. By incorporating momentum term, the momentum factor is adaptively adjusted to make it have better separation performance. The simulation results show that compared with the traditional algorithm, the proposed algorithm can better balance the contradiction between convergence speed and steady-state error in non-stationary environment, and has better separation performance. In the case of obvious disturbance in the mixed system, the algorithm can effectively improve the shortcomings of the traditional algorithm. In summary, constrained blind separation algorithm using variable step size and variable momentum factor proposed in this paper is effective.
VL  - 8
IS  - 4
ER  -

Copy | Download