Lagrange exponential stability of quaternion‐valued memristive neural networks with time delays

Wei, Ruoyu; Cao, Jinde; Huang, Chuangxia

doi:10.1002/mma.6463

Cited by 37 publications

(16 citation statements)

References 31 publications

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“…  are the mean and standard deviation of the variable, respectively [10]. Then the mathematical model of the expected average space calculation of the reliability index can be expressed as follows:…”

Section: The Geometric Meaning Of Reliability Indicatorsmentioning

confidence: 99%

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Jian-xia

2023

Applied Mathematics and Nonlinear Sciences

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This paper refers to the Lagrangian mathematical model and the Rackwitz-Fiessler transform model in modeling advanced mathematics applications. In this paper, the Lagrangian interpolation method and Rackwitz-Fiessler transform are used to calculate the correlation coefficient efficiently. The purpose of this algorithm is to speed up the process of probabilistic modeling. This paper uses integral probability transformation to characterize the output's uncertainty by the production's joint distribution function. The purpose of this process is to improve the reliability of the calculation. Through the algorithm analysis, it is found that the method is reasonable and efficient.

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Section: The Geometric Meaning Of Reliability Indicatorsmentioning

confidence: 99%

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Jian-xia

2023

Applied Mathematics and Nonlinear Sciences

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“…In this paper, a Gaussian mixture model is selected to achieve background subtraction based on the particularity of aerobics video images [8]. The principle is to use K Gaussian models to represent the features of each pixel in the aerobics video image.…”

Section: Background Subtraction and Noise Reduction For Video Imagesmentioning

confidence: 99%

Optimization System of Strength and Flexibility Training in Aerobics Course Based on Lagrangian Mathematical Equation

Han

2022

Applied Mathematics and Nonlinear Sciences

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In this paper, the Lagrangian mathematical equation is used to construct a feature extraction model for the flexibility of aerobics athletes. At the same time, this paper uses machine vision to identify and extract feature points of aerobics movements. This paper realizes image feature recognition through multi-dimensional pixel information decomposition. At the same time, we realize the radian trajectory positioning of the aerobics action image based on the Lagrangian equation. The experimental research shows that the algorithm proposed in this paper has higher accuracy and better localization performance when recognizing the radian trajectory of aerobics movements. The algorithm improves the optimization and correction ability of aerobics movements.

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“…erefore, we have completed the proof. (11), it is easy to know that chattering behaviors derived from the symbolic function in event-triggered controller (6) can be effectively reduced by choosing small parameters π i .…”

Section: Theorem 1 When Assumptions 1 and 2 Hold If The Parameters P I And Q I Of The Control Gain Matrices Satisfymentioning

confidence: 99%

“…In recent ten years, memristor-based neural networks, also known as memristive neural networks (MNNs), have attracted growing attention by the advantage of human brain simulation. e stability of neural networks as a crucial prerequisite to the application is very important, and the problem for stability analysis of MNNs has been widely studied by many researchers [5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Exponential Synchronization of Memristive Neural Networks with Discrete and Distributed Time-Varying Delays via Event-Triggered Control

Wen-bo

2021

Discrete Dynamics in Nature and Society

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In this paper, we investigate the exponential synchronization problem of memristive neural networks (MNNs) with discrete and distributed time-varying delays under event-triggered control. An event-triggered controller with the static and dynamic event-triggering conditions is designed to improve the efficiency of resource utilization. By constructing a new Lyapunov function, some sufficient criteria are obtained to realize the exponential synchronization of considered drive-response MNNs under the designed event-triggered controller. In addition, the Zeno behavior will not occur by proving that the event-triggering interval has a positive lower bound under different event-triggering conditions. Finally, a numerical example is provided to prove the validity of our theoretical results.

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Lagrange exponential stability of quaternion‐valued memristive neural networks with time delays

Cited by 37 publications

References 31 publications

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Optimization System of Strength and Flexibility Training in Aerobics Course Based on Lagrangian Mathematical Equation

Exponential Synchronization of Memristive Neural Networks with Discrete and Distributed Time-Varying Delays via Event-Triggered Control

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