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dc.contributor.authorMohamad, Sannay
dc.contributor.authorAkca, Haydar
dc.contributor.authorCovachev, Val´ery
dc.date.accessioned2018-03-26T06:02:22Z
dc.date.available2018-03-26T06:02:22Z
dc.date.issued2012-11-12
dc.identifier.urihttps://dspace.adu.ac.ae/handle/1/823
dc.descriptionMohamad, S., Akça, H., & Covachev, V. (2009). Discrete-time Cohen-Grossberg neural networks with transmission delays and impulses. Tatra Mountains Mathematical Publications, 43(1), 145-161.en_US
dc.description.abstractA discrete-time analogue is formulated for an impulsive Cohen- -Grossberg neural network with transmission delay in a manner in which the global exponential stability characterisitics of a unique equilibrium point of the network are preserved. The formulation is based on extending the existing semi- discretization method that has been implemented for computer simulations of neu- ral networks with linear stabilizing feedback terms. The exponential convergence in the p-norm of the analogue towards the unique equilibrium point is analysed by exploiting an appropriate Lyapunov sequence and properties of an M -matrix. The main result yields a Lyapunov exponent that involves the magnitude and frequency of the impulses. One can use the result for deriving the exponential sta- bility of non-impulsive discrete-time neural networks, and also for simulating the exponential stability of impulsive and non-impulsive continuous-time networks.en_US
dc.language.isoen_USen_US
dc.publisherVersitaen_US
dc.subjectCohen-Grossberg neural networksen_US
dc.subjectDiscrete-Time Analoguesen_US
dc.subjectLyapunov Exponents.en_US
dc.titleDISCRETE-TIME COHEN-GROSSBERG NEURAL NETWORKS WITH TRANSMISSION DELAYS AND IMPULSESen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.2478/v10127-009-0034-5


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