Stability analysis of delayed neural networks with slope-bounded activation functions

نویسندگان

  • Xiang Xie
  • Rong Zhang
چکیده

This paper deals with the global asymptotic stability problem of delayed neural networks with unbounded activation functions and network parameter uncertainties. New stability criteria for global asymptotic stability of the delayed neural networks are derived by employing suitable Lyapunov functionals. These results reported in this paper can be regarded as generalizations of some existing stability results. The effectiveness and usefulness of the obtained results can be verified by comparing our results with the previously published results. Subjects: Computer Mathematics; Non-Linear Systems; Dynamical Systems

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays

This paper investigates the absolute exponential stability of a general class of delayed neural networks, which require the activation functions to be partially Lipschitz continuous and monotone nondecreasing only, but not necessarily differentiable or bounded. Three new sufficient conditions are derived to ascertain whether or not the equilibrium points of the delayed neural networks with addi...

متن کامل

Dynamical Behaviors of Delayed Neural Network Systems with Discontinuous Activation Functions

In this letter, without assuming the boundedness of the activation functions, we discuss the dynamics of a class of delayed neural networkswith discontinuous activation functions. A relaxed set of sufficient conditions is derived, guaranteeing the existence, uniqueness, and global stability of the equilibrium point. Convergence behaviors for both state and output are discussed. The constraints ...

متن کامل

Novel delay-dependent criteria for global robust exponential stability of delayed cellular neural networks with norm-bounded uncertainties

The problem ensuring the global robust exponential stability of a class of delayed cellular neural networks with norm-bounded uncertainties is studied. Without assuming the boundedness of the activation functions, by applying the idea of vector Lyapunov function and linear matrix inequality (LMI) techniques, some sufficient conditions for the global robust exponential stability of uncertain cel...

متن کامل

Robust exponential stability criterion for uncertain neural networks with discontinuous activation functions and time-varying delays

This paper considers the global robust exponential stability of time-varying delayed neural networks with discontinuous activation functions and norm-bounded uncertainties. Based on the Lyapunov– Krasovskii stability theory, we originally analyze the global robust exponential stability of discontinuous neural networks with time-varying delays in view of the linear matrix inequalities given to v...

متن کامل

Global Asymptotic Stability of a General Class of Recurrent Neural Networks With Time-Varying Delays

In this paper, the existence and uniqueness of the equilibrium point and its global asymptotic stability are discussed for a general class of recurrent neural networks with time-varying delays and Lipschitz continuous activation functions. The neural network model considered includes the delayed Hopfield neural networks, bidirectional associative memory networks, and delayed cellular neural net...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017