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In light of neuroimaging studies and new conceptual frameworks, these results demonstrate an age-related increase of controlled processing of standing associated with greater intermittent adjustments.
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This paper extends some traditional anti-synchronization criteria by using intermittent adjustment feedback control.
Unfortunately, there are few papers considering the finite-time anti-synchronization of neural networks via feedback control with intermittent adjustment.
In the intermittent adjustment feedback controller (7) and (8), the parameter k plays an important part in improving the convergence speed.
It is important to note that the intermittent adjustment feedback control can reduce the control time and cost rather than the continuous control.
A simple intermittent adjustment feedback controller is designed to ensure the drive-response systems realize anti-synchronization in a finite time.
A simple intermittent adjustment feedback controller is designed to control the states of two systems to achieve anti-synchronization within a finite time.
At the same time, the state trajectories of system (18) and (19) can be drawn without the intermittent adjustment feedback controller (8) in Figure 9.
In this simulation, the values of the parameters for the intermittent adjustment feedback controller (8) are taken as (beta= 25.1), (k = 12), (alpha= 0.95), (T = 2) and (theta= 0.6).
Furthermore, by applying an inequality technique and the Lyapunov stability theorem, the finite-time anti-synchronization can be realized between the drive and response systems by designing an intermittent adjustment feedback controller.
(u(t) = ({u_{1}}(t),{u_{2}}(t), ldots,{u_{n}}(t))^{T}) is an intermittent adjustment feedback controller that will be designed to achieve the anti-synchronization between drive-response systems.
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