Fixed‐time synchronization of neural networks with time delay via quantized intermittent control

In this paper, fixed‐time synchronization of nonlinear stochastic coupling multilayer neural networks is studied. The neural subnets in the multilayer networks are delay Cohen–Grossberg neural networks (DCGNNs). To overcome uncertain factors, we designed an adaptive delay‐dependent controller in synchronization. To describe constraints of communication and other related problems in networks, which are due to limitations for bit rates and bandwidths in communication channels, an adaptive fixed‐time control strategy is purposed by introducing quantization signal input. A theoretical framework about fixed‐time synchronization in multilayer delay Cohen–Grossberg neural networks (MDCGNNs) is established. We find that fixed settling time is related to the scale of MDCGNNs, characteristics of the designed controller parameters, and level of quantization. Finally, the effective of the theoretical framework is validated in an example.

“…A theoretical framework about fixed-time synchronization in MDCGNNs is established. In the proof, the more appropriate inequalities to scale, the better results can be got [18][19][20].…”

Section: Discussionmentioning

confidence: 99%

Fixed‐time synchronization in multilayer networks with delay Cohen–Grossberg neural subnets via adaptive quantitative control

Tan,

Zhou,

et al. 2023

“…In [9], by making use of BAM NNs, an efficient reversible adaptive video watermarking scheme for multiple watermarks is analyzed. In many practical control systems, time delay exists unavoidably if there is the transmission of information between different parts of the system [10–12]. In view of this, the global robust stability analysis of BAM NNs with multiple time delays has been analyzed by Thoiyab et al [13].…”

Section: Introductionmentioning

confidence: 99%

Extended dissipative output‐feedback control for discrete‐time bidirectional associative memory neural networks via delay‐partitioning approach

Adhira

Nagamani

2023

This paper is concerned with the analysis of an extended dissipativity performance for a class of bidirectional associative memory (BAM) neural networks (NNs) having time‐varying delays. To achieve this, the idea of the delay‐partitioning approach is used, where the range of time‐varying delay factors is partitioned into a finite number of equidistant subintervals. A delay‐partitioning based Lyapunov–Krasovskii function is introduced on these intervals, and some new delay‐dependent extended dissipativity results are established in terms of linear matrix inequalities, which also depend on the partition size of the delay factor. Further, numerical examples are performed to acknowledge the extended dissipativity performance of delayed discrete‐time BAM NN; further, four case studies were explored with their simulations to validate the impact of the delay‐partitioning approach.

“…Notably, time delays within a system can readily induce instability, manifesting as oscillations and chaotic phenomena, which impedes the advancement of time-delay systems in practical applications. Recently, numerous findings on time-delay systems have been reported [1][2][3], particularly in the context of neural networks [4][5][6][7], man-Co-first authors: Zheqi Yu and Song Ling contribute equally to this work.…”

Section: Introductionmentioning

confidence: 99%

“…Notably, time delays within a system can readily induce instability, manifesting as oscillations and chaotic phenomena, which impedes the advancement of time‐delay systems in practical applications. Recently, numerous findings on time‐delay systems have been reported [1–3], particularly in the context of neural networks [4–7], manufacturing processes [8], secure communication [9], biology [10], and information technology [11]. Khadra et al examined the influence of delay on impulsive synchronization and proposed sufficient conditions for mitigating the delay issue in secure communication [9].…”

Section: Introductionmentioning

confidence: 99%

Exponential stability of time‐delay systems with flexible delayed impulse

Ling

Liu

2023

The problem of exponential stability for time‐delay systems with flexible delayed impulse control is investigated. Unlike the conventional Razumikhin‐type inequality, variable parameter based on the flexible impulsive gain is introduced. Sufficient conditions for exponential stability are developed for a class of time‐delay systems, for which the size of delay is not limited by impulsive intervals. A flexible impulse control scheme is developed by utilizing the flexible impulsive gain and time‐varying delays. When the system is disturbed by the impulse interferences, both the impulse gain and impulse delay can be adjusted accordingly to make the system exponential stable. The effectiveness of the present results is illustrated by two numerical examples and an application.