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Improved Blind Source Separation Based on Non-Holonomic Natural Gradient Algorithm with Variable Step Size

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Proceedings of 2013 Chinese Intelligent Automation Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 256))

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Abstract

The traditional natural gradient algorithm works badly when the source signal amplitude changes rapidly or becomes zero at a certain time. In addition, it cannot resolve very well the contradiction between the convergence speed and the error in steady state because the step-size is fixed. In order to solve the above problems, this paper proposes an improved blind source separation algorithm based on non-holonomic natural gradient by choosing an adaptive step-size and a suitable nonlinear activation function. Simulation result demonstrates that the new algorithm performance is superior to the traditional natural gradient algorithm.

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Acknowledgments

1. National Natural Science Foundation of China (11273001, 61074073, 61273164).

2. New Century Excellent Talents in University (NCET-10-0306), Ministry of Education, China.

Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China

    Ce Ji & Kun Yang

  2. Troops 65521 PLA, Liaoyang, 111000, Liaoning, China

    Baocheng Tang

  3. Allwin Telecommunication Co., Ltd, Shenyang, 110007, Liaoning, China

    Mingbo Sha

Authors
  1. Ce Ji
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  2. Baocheng Tang
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  3. Kun Yang
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  4. Mingbo Sha
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Corresponding author

Correspondence to Kun Yang .

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Editors and Affiliations

  1. , Department of Computer Science, Tsinghua University, Qinghua, Beijing, 100084, China, People's Republic

    Zengqi Sun

  2. Tsinghua University, Qinghua, Beijing, 100084, China, People's Republic

    Zhidong Deng

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© 2013 Springer-Verlag Berlin Heidelberg

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Ji, C., Tang, B., Yang, K., Sha, M. (2013). Improved Blind Source Separation Based on Non-Holonomic Natural Gradient Algorithm with Variable Step Size. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_84

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  • DOI: https://doi.org/10.1007/978-3-642-38466-0_84

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38465-3

  • Online ISBN: 978-3-642-38466-0

  • eBook Packages: EngineeringEngineering (R0)

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