Global exponential stability of high order Hopfield type neural networks

@article{Xu2006GlobalES,
  title={Global exponential stability of high order Hopfield type neural networks},
  author={Bingji Xu and Xinzhi Liu and Xiaoxin Liao},
  journal={Applied Mathematics and Computation},
  year={2006},
  volume={174},
  pages={98-116}
}
Highly Cited
This paper has 100 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 42 extracted citations

Global exponential robust stability of stochastic high-order hopfield neural networks with S-type distributed time delays

Proceedings of the 33rd Chinese Control Conference • 2014
View 10 Excerpts
Highly Influenced

Novel Exponential Stability Criteria of High-Order Neural Networks With Time-Varying Delays

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) • 2011
View 8 Excerpts
Highly Influenced

Multistability in Networks With Self-Excitation and High-Order Synaptic Connectivity

IEEE Transactions on Circuits and Systems I: Regular Papers • 2010
View 4 Excerpts
Highly Influenced

Novel delay-dependent robust stability criteria of hopfield neural networks with time-varying delay

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) • 2017

101 Citations

01020'08'11'14'17
Citations per Year
Semantic Scholar estimates that this publication has 101 citations based on the available data.

See our FAQ for additional information.