Reduced-order state estimation of delayed recurrent neural networks. Academic Article uri icon


  • Different from the widely-studied full-order state estimator design, this paper focuses on dealing with the reduced-order state estimation problem for delayed recurrent neural networks. By employing an integral inequality, a delay-dependent design approach is proposed, and global asymptotical stability of the resulting error system is guaranteed. It is shown that the gain matrix of the reduced-order state estimator is determined by the solution of a linear matrix inequality. Numerical examples are provided to illustrate the effectiveness of the developed result.

published proceedings

  • Neural Netw

author list (cited authors)

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

citation count

  • 7

complete list of authors

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

publication date

  • February 2018