Finite-time stabilization and energy consumption estimation for delayed neural networks with bounded activation function.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper concentrates on finite-time stabilization and energy consumption estimation for one type of delayed neural networks (DNNs) with bounded activation function. Under the bounded activation function condition and using the comparison theorem, a new switch controller is proposed to ensure the finite-time stability of the considered DNNs. Furthermore, the energy consumption produced in system controlling is estimated by inequality techniques. We generalize the previous results about the problem of finite-time stabilization and energy consumption estimation for neural networks. Ultimately, two numerical simulations are carried out to verify the validity of our results.

Authors

  • Chongyang Chen
    School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: ccycumt@163.com.
  • Song Zhu
    College of Sciences, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: songzhu82@gmail.com.
  • Min Wang
    National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, Wenzhou University, Wenzhou 325035, China.
  • Chunyu Yang
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
  • Zhigang Zeng