Exponential stabilization of delayed recurrent neural networks: A state estimation based approach. Academic Article uri icon


  • This paper is concerned with the stabilization problem of delayed recurrent neural networks. As the states of neurons are usually difficult to be fully measured, a state estimation based approach is presented. First, a sufficient condition is derived such that the augmented system under consideration is globally exponentially stable. Then, by employing a decoupling technique, the gain matrices of the controller and state estimator are achieved by solving some linear matrix inequalities. Finally, a delayed neural network with chaotic behaviors is exploited to demonstrate the applicability of the developed result.

published proceedings

  • Neural Netw

altmetric score

  • 3

author list (cited authors)

  • Huang, H. e., Huang, T., Chen, X., & Qian, C.

citation count

  • 51

complete list of authors

  • Huang, He||Huang, Tingwen||Chen, Xiaoping||Qian, Chunjiang

publication date

  • December 2013