| dc.contributor.author | S, Mohamad, | |
| dc.contributor.author | Akca, Haydar | |
| dc.contributor.author | Covachev, V | |
| dc.date.accessioned | 2022-01-05T17:19:18Z | |
| dc.date.available | 2022-01-05T17:19:18Z | |
| dc.date.issued | 2008-08 | |
| dc.identifier.citation | Mohamad, 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.identifier.uri | https://dspace.adu.ac.ae/handle/1/2129 | |
| dc.description | Numerical (or computer) simulations of continuous-time neural networks governed by differential equations involving transmission delays (i.e., discrete or
fixed delays, time-varying delays and distributed delays) have been developed
steadily over the years [14]–[21], [23]–[3 | en_US |
| dc.description.abstract | . A 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 semidiscretization method that has been implemented for computer simulations of neural 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 stability of non-impulsive discrete-time neural networks, and also for simulating the
exponential stability of impulsive and non-impulsive continuous-time network | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Tatra Mountains Mathematical Publication | en_US |
| dc.subject | Cohen-Grossberg neural networks | en_US |
| dc.subject | Delays | en_US |
| dc.subject | Discrete-time analogues | en_US |
| dc.subject | Lyapunov exponent | en_US |
| dc.title | Discrete-time Cohen-Grossberg neural networks with transmission delays and impulses | en_US |
| dc.title.alternative | Tatra Mt. Math. Publ. 43 (2009), 145–161 | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | 10.2478/v10127-009-0034-5 | |
