Results 11 to 20 of about 438 (172)
Exponential synchronization of memristive Cohen–Grossberg neural networks with mixed delays [PDF]
Cognitive Neurodynamics, 2014 Xinsong Yang, Jinde Cao, Wenwu Yu
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Stability Analysis of Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays
IEEE Access, 2022 By improving a previously introduced Lyapunov functional,this paper addressed the stability issue about neutral-type Cohen-Grossberg neural networks with multiple time-varying delays in the states of neurons and the time derivative of states of neurons ...
Binbin Gan, Biao Xu, Hao Chen
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Mathematics, 2023 This article is concerned with fixed-time synchronization and preassigned-time synchronization of Cohen–Grossberg quaternion-valued neural networks with discontinuous activation functions and generalized time-varying delays.
Shichao Jia, Cheng Hu, Haijun Jiang
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Bifurcation of a Cohen‐Grossberg Neural Network with Discrete Delays [PDF]
Abstract and Applied Analysis, 2012 A simple Cohen‐Grossberg neural network with discrete delays is investigated in this paper. The existence of local Hopf bifurcations is first considered by choosing the appropriate bifurcation parameter, and then explicit formulas are given to determine the direction of Hopf bifurcation and stability of the periodic solutions.
Liu, Qiming, Zheng, Wang
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Discrete Dynamics in Nature and Society, Volume 2023, Issue 1, 2023., 2023 In this paper, the settling time estimation of synchronization issues for inertial memristive neural networks (IMNNs) with mixed time‐varying delays is investigated. First, by using a new reduced order approach and introducing free‐weighted coefficients ηi and ξi into variable transformation, the original second‐order derivative system is transformed ...
Tiecheng Zhang, Dasong Huang, Ya Jia
wiley +1 more source
Stability Analysis of Neutral-Type Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays
IEEE Access, 2020 This paper deals with the problem for stability of neutral-type Cohen-Grossberg neural networks involving delay parameters. In the neutral-type neural networks, the states of the neurons involve multiple time-varying delays and time derivative of states ...
Li Wan, Qinghua Zhou
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Stability Analysis of Cohen–Grossberg Type BAM Neural Network with Piecewise Constant Argument
Discrete Dynamics in Nature and Society, Volume 2023, Issue 1, 2023., 2023 This paper introduces the stability problems of Cohen–Grossberg type BAM neural network (BAMCGNN) with piecewise constant argument (PCA). By employing the homeomorphism theory, sufficient conditions for the existence and uniqueness of the equilibrium point are obtained; using inequality technique and Lyapunov method, sufficient stability criteria for ...
Wenqing Zheng +3 more
wiley +1 more source
General stability for a Cohen–Grossberg neural network system
Arabian Journal of Mathematics, 2023 AbstractOf concern is a Cohen–Grossberg neural network (CGNNs) system taking into account distributed and discrete delays. The class of delay kernels ensuring exponential stability existing in the previous papers is enlarged to an extended class of functions guaranteeing more general types of stability.
Mohammed D. Kassim, Nasser-Eddine Tatar
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Treating the most vulnerable: A discursive review of experimental pain in Alzheimer’s disease
Nursing Open, Volume 9, Issue 2, Page 942-949, March 2022., 2022 Abstract Aim The purpose of this manuscript is to summarize research on how experimental pain is experienced by adults with Alzheimer's disease (AD) and to translate results into implications for nurses. Design This discursive review synthesizes the results of three previous research studies exploring experimental pain in adults with AD.
Wm. Larkin Iversen +9 more
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Impulsive Fractional Cohen-Grossberg Neural Networks: Almost Periodicity Analysis
Fractal and Fractional, 2021 In this paper, a fractional-order Cohen–Grossberg-type neural network with Caputo fractional derivatives is investigated. The notion of almost periodicity is adapted to the impulsive generalization of the model.
Ivanka Stamova +3 more
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