Exponential Stability of Hopfield Neural Network Model with Non-Instantaneous Impulsive Effects
نویسندگان
چکیده
We introduce a non-instantaneous impulsive Hopfield neural network model in this paper. Firstly, we prove the existence and uniqueness of an almost periodic solution model. Secondly, that is exponentially stable. Finally, give example
منابع مشابه
Globally exponential stability for Hopfield neural networks with delays and impulsive perturbations
In this paper, we consider the global exponential stability of the equilibrium point of Hopfield neural networks with delays and impulsive perturbation. Some new exponential stability criteria of the system are derived by using the Lyapunov functional method and the linear matrix inequality approach for estimating the upper bound of the derivative of Lyapunov functional. Finally, we illustrate ...
متن کاملGlobal Exponential Stability of Delay Neural Networks with Impulsive Perturbations
This paper considers the global exponential stability of delay neural networks with impulsive perturbations. By establishing a new impulsive delay inequality which is different from the earlier publication, we obtain some new sufficient conditions ensuring exponential stability of the equilibrium point for such neural networks. The neural networks model considered include the impulsive delay Ho...
متن کاملAbsolute Stability of Hopfield Neural Network
This paper presents some new results for the absolute stability of Hopfield neural networks with activation functions chosen from sigmoidal functions which have unbounded derivatives. Detailed discussions are also given to the relation and difference of absolute stabilities between neural networks and Lurie systems with multiple nonlinear controls. Although the basic idea of the absolute stabil...
متن کاملExponential stability of implicit Euler, discrete-time Hopfield neural networks
The exponential stability of continuous-time Hopfield neural networks is not preserved when implemented on digital computers by means of explicit numerical methods, whereas the implicit (or backward) Euler method preserves this exponential stability under exactly the same sufficient conditions as those previously obtained for the continuous model. The proof is based on the nonlinear measure app...
متن کاملExponential Stability of Discrete-Time Hopfield Neural Networks
In this paper, some sufficient conditions for the local and global exponential stability of the discrete-time Hopfield neural networks with general activation functions are derived, which generalize those existing results. By means of M-matrix theory and some inequality analysis techniques, the exponential convergence rate of the neural networks to the equilibrium is estimated, and for the loca...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Axioms
سال: 2023
ISSN: ['2075-1680']
DOI: https://doi.org/10.3390/axioms12020115