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An Improved Diffusion Affine Projection Estimation Algorithm for Wireless Sensor Networks

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Abstract

Affine projection algorithms have shown robustness against highly correlated input signals. To make the affine projection algorithm applicable for parameter estimation in wireless sensor networks, this work proposed a novel distributed affine projection algorithm by using the adapt-then-combine (ATC) scheme of the diffusion strategy. However, poorly performing nodes can potentially degrade to estimation performance. Thus, we develop an improved ATC diffusion affine projection algorithm (improved ATC-dAPA) with adaptive node selection to maintain the estimation accuracy. The mean and mean square deviation of the proposed algorithm are analyzed. The numerical simulation results illustrate that the proposed algorithm can achieve more accurate estimations than several related algorithms.

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Authors and Affiliations

  1. College of Artificial Intelligence, Southwest University, Chongqing, 400715, China

    Limei Hu, Feng Chen & Shukai Duan

  2. College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Limei Hu, Feng Chen, Lidan Wang & Jiagui Wu

  3. Brain-Inspired Computing and Intelligent Control Key Laboratory, Southwest University, Chongqing, 400715, China

    Limei Hu, Feng Chen & Lidan Wang

  4. Chongqing Collaborative Innovation Center for Brain Science, Chongqing, 400715, China

    Limei Hu & Feng Chen

Authors
  1. Limei Hu
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  2. Feng Chen
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  3. Shukai Duan
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  4. Lidan Wang
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  5. Jiagui Wu
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Correspondence to Feng Chen.

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This work was supported in part by the National Key R&D Program of China (Nos. 2018YFB1306600, 2018YFB1306604), National Natural Science Foundation of China (Grant No. 61875168) and Chongqing Research Program of Basic Research and Frontier Technology (No. cstc2017jcyjAX0265).

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Hu, L., Chen, F., Duan, S. et al. An Improved Diffusion Affine Projection Estimation Algorithm for Wireless Sensor Networks. Circuits Syst Signal Process 39, 3173–3188 (2020). https://doi.org/10.1007/s00034-019-01317-5

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  • DOI: https://doi.org/10.1007/s00034-019-01317-5

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