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Continuous-Time Multi-agent Network for Distributed Least Absolute Deviation

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Advances in Neural Networks – ISNN 2015 (ISNN 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9377))

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Abstract

This paper presents a continuous-time multi-agent network for distributed least absolute deviation (DLAD). The objective function of the DLAD problem is a sum of many least absolute deviation functions. In the multi-agent network, each agent connects with its neighbors locally and they cooperate to obtain the optimal solutions with consensus. The proposed multi-agent network is in fact a collective system with each agent being considered as a recurrent neural network. Simulation results on a numerical example are presented to illustrate the effectiveness and characteristics of the proposed distributed optimization method.

This work was supported in part by the National Natural Science Foundation of China under Grant 61473333, by the Program for New Century Excellent Talents in University of China under Grant NCET-12-0114, and by the Fundamental Research Funds for the Central Universities of China under Grant 2015QN035.

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Author information

Authors and Affiliations

  1. School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Qingshan Liu

  2. Department of Basic Courses, Wannan Medical College, Wuhu, 241000, Anhui, China

    Yan Zhao

  3. State Key Lab. of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Long Cheng

Authors
  1. Qingshan Liu
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  2. Yan Zhao
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  3. Long Cheng
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Corresponding author

Correspondence to Qingshan Liu .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Xiaolin Hu

  2. Fuzhou University, Fuzhou, China

    Yousheng Xia

  3. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China

    Yunong Zhang

  4. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Dongbin Zhao

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© 2015 Springer International Publishing Switzerland

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Liu, Q., Zhao, Y., Cheng, L. (2015). Continuous-Time Multi-agent Network for Distributed Least Absolute Deviation. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_48

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25392-3

  • Online ISBN: 978-3-319-25393-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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