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Figure 1 The trajectory of solution of system (3.2) Figure 2 The trajectory of solution of system (3.2) without disturbance.
Then difference of along trajectory of solution of (3.1) is given by (3.4).
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Figure 1 shows the trajectories of solution of Example 4.1 with disturbance.
Figure 2 shows the trajectories of solution of Example 4.1 without disturbance.
Then Theorem 3.4 is satisfied with (c_{1}=1, c_{2}=1,a=0.5,q=1.6, beta=0.8, p=1,rho( Vert w(k) Vert ) leq 0.9). Figure 3 shows the trajectories of solution of Example 4.2. Figure 4 shows the trajectories of solution of system (2.1) without disturbance.
Moreover, the solution x ( t, ϕ ) of the system satisfies ∥ x ( t, ϕ ) ∥ ≤ 2.3257 e − 0.3 t ∥ ϕ ∥, ∀ t ≥ 0. The trajectories of solution of switched recurrent neural networks is shown in Figure 1, respectively.
Moreover, the solution x ( t, ϕ ) of the system satisfies E { ∥ x ( t, ϕ ) ∥ } ≤ E { 1.0239 e − 1.5 t ∥ ϕ ∥ }, ∀ t ∈ R +. (The trajectories of solution of switched stochastic systems is shown in Figure 1, respectively).
Numerous graphical illustrations of stability regions and trajectories of solutions are plotted.
In Figure 5 two trajectories of solutions of (3.10) are shown with the initial conditions,, and,.
Two corresponding trajectories of solutions are shown in Figure 7 with the initial conditions,, and,.
In Figure 6 two trajectories of solutions of (3.10) with the initial conditions,, and, are shown in the point with,.
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