Stability of Cohen-Grossberg neural networks with time-varying delays. Academic Article

abstract

• In this paper, we investigate the existence and stability of the equilibrium point of Cohen-Grossberg neural networks with time-varying delays. Under easily verified conditions, exponential stability is obtained when the delay is finite, while asymptotic stability is obtained when the delay is infinite. Moreover, the stability obtained is robust. The only condition for the delay term is continuity. The results obtained here improve and extend to those in the literature.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Huang, T., Chan, A., Huang, Y. u., & Cao, J.

citation count

• 74

complete list of authors

• Huang, Tingwen||Chan, Andrew||Huang, Yu||Cao, Jinde

publication date

• October 2007

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Algorithms
• Artificial Intelligence
• Computer Simulation
• Information Storage And Retrieval
• Markov Chains
• Models, Theoretical
• Neural Networks, Computer
• Nonlinear Dynamics
• Pattern Recognition, Automated
• Signal Processing, Computer-Assisted
• Stochastic Processes
• Systems Theory
• Time Factors

PubMed Central ID

• 17720364

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2007.07.005

start page

• 868

end page

• 873

volume

• 20

issue

• 8

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.neunet.2007.07.005