Impulsive Control for a Class of Cellular Neural Networks with Proportional Delay

Guan, Kaizhong; Wang, Qisheng

doi:10.1007/s11063-017-9776-2

Cited by 9 publications

(4 citation statements)

References 43 publications

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Section: Applications In Neural Networkmentioning

confidence: 99%

“…In [117][118][119][120][121], the authors investigated the stability of neural networks in the form of system (22) or similar. For more information about the functions in system (22), refer to [117][118][119][120][121], respectively. In order to better study the neural network system, various techniques and methods have been constantly proposed or developed.…”

Section: Applications In Neural Networkmentioning

confidence: 99%

“…By employing Lyapunov-Razumikhin functions together with differential inequalities, some sufficient conditions of robust exponential stability were obtained. In [120], proportional delay is considered in neural networks, to put it simply, x(t − τ(t)) is replaced by x(qt), where q ∈ (0, 1) is proportional delay factor and qt = t − (1 − q)t, in which (1 − q)t corresponds to the time delay required in processing and transmitting a signal from the jth cell to the ith cell. By using the improved Lyapunov-Razumikhin method, some sufficient conditions ensuring the existence, uniqueness and globally asymptotic stability of the concerned neural networks are presented.…”

Section: Applications In Neural Networkmentioning

confidence: 99%

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Stability of Differential Systems with Impulsive Effects

Li,

Hui,

2023

Mathematics

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In this paper, a brief survey on the stability of differential systems with impulsive effects is provided. A large number of research results on the stability of differential systems with impulsive effects are considered. These systems include impulsive differential systems, stochastic impulsive differential systems and differential systems with several specific impulses (non-instantaneous impulses, delayed impulses, impulses suffered by logic choice and impulse time windows). The stability issues as well as the applications in neural networks are discussed in detail.

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Section: Applications In Neural Networkmentioning

confidence: 99%

Section: Applications In Neural Networkmentioning

confidence: 99%

Section: Applications In Neural Networkmentioning

confidence: 99%

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Stability of Differential Systems with Impulsive Effects

Li,

Hui,

2023

Mathematics

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“…[10][11][12][13] X. Li et al 5 designed impulsive control and derived the global exponential stability. Guan and Wang 14 studied globally asymptotically stable via the Lyapunov and Razumukhin technique for impulsive control of the cellular neural network with proportional delay. Further, the study refers to Guan, 15 X. Li et al, 16 and D. Li et al 17 However, the random impulses are made considerable attention in the nonlinear differential systems; the impulses do not always occur at fixed time points on the system state; it is possible to occur in random time points on the system state because in the real-world system states are often change randomly.…”

Section: Introductionmentioning

confidence: 99%

Exponential stability of random impulsive pantograph equations

Vinodkumar

Senthilkumar

Liu

et al. 2021

Math Methods in App Sciences

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In this paper, we study the pth moment exponential stable and pth moment weakly exponential stable results for the random impulsive pantograph delay differential equations (RIPDDEs). Further, we obtained some sufficient conditions by using the method of Lyapunov and Razumukhin technique. Finally, we give several numerical examples with their simulations are provided to illustrate the effectiveness of the proposed results.

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