
doi: 10.1002/mma.4630
This paper deals with finite‐time stabilization results of delayed Cohen‐Grossberg BAM neural networks under suitable control schemes. We propose a state‐feedback controller together with an adaptive‐feedback controller to stabilize the system of delayed Cohen‐Grossberg BAM neural networks. Stabilization conditions are derived by using Lyapunov function and some algebraic conditions. We also estimate the upper bound of settling time functional for the stabilization, which depends on the controller schemes and system parameters. Two illustrative examples and numerical simulations are given to validate the success of the derived theoretical results.
Control problems for functional-differential equations, adaptive-control, Control/observation systems governed by functional-differential equations, Stability theory of functional-differential equations, Adaptive control/observation systems, time-delay, Stabilization of systems by feedback, Cohen-Grossberg BAM neural networks, Neural networks for/in biological studies, artificial life and related topics, stabilization
Control problems for functional-differential equations, adaptive-control, Control/observation systems governed by functional-differential equations, Stability theory of functional-differential equations, Adaptive control/observation systems, time-delay, Stabilization of systems by feedback, Cohen-Grossberg BAM neural networks, Neural networks for/in biological studies, artificial life and related topics, stabilization
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
