Volume 44 Issue 3
Mar.  2018
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LU Cheng, XU Tingxue, WANG Honget al. A fault diagnosis model of plasticity echo state network based on L1/2-norm regularization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(3): 535-541. doi: 10.13700/j.bh.1001-5965.2017.0214(in Chinese)
Citation: LU Cheng, XU Tingxue, WANG Honget al. A fault diagnosis model of plasticity echo state network based on L1/2-norm regularization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(3): 535-541. doi: 10.13700/j.bh.1001-5965.2017.0214(in Chinese)

A fault diagnosis model of plasticity echo state network based on L1/2-norm regularization

doi: 10.13700/j.bh.1001-5965.2017.0214
Funds:

National Natural Science Foundation of China 51605487

Shandong Provincial Natural Science Foundation, China ZR2016FQ03

More Information
  • Corresponding author: XU Tingxue, E-mail: xtx-yt@163.com
  • Received Date: 10 Apr 2017
  • Accepted Date: 11 Aug 2017
  • Publish Date: 19 Oct 2017
  • In order to improve the dynamic adaptability of reservoir, overcome the ill-posed problems of output weights in echo state network (ESN), and balance the fitting and generalization ability, a fault diagnosis model of plasticity echo state network based on L1/2-norm regularization is presented. BCM rule was introduced into the reservoir construction to train the connection weight matrix. Meanwhile, the L1/2-norm penalty term was added to the objective function in order to improve the sparsification efficiency. An iterative numerical oscillation problem was solved by using a smoothing L1/2 regularizer, and finally the model was solved by using the half threshold iteration method. The model is applied to the fault diagnosis of airborne radio station, and the simulation results prove the validity and superiority of the model.

     

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