Asymptotic Behavior of a Neural Network Model with Dynamical Threshold

نویسندگان

  • BINXIANG DAI
  • XIANGZHENG QIAN
  • LIHONG HUANG
  • SHANGJIANG GUO
چکیده

Necessary and sufficient conditions are obtained for the existence of a globally asymptotically stable equilibrium of a class of delay differential systems modelling the action of two neurons with dynamical threshold effects.

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

Global Asymptotic and Exponential Stability of Tri-Cell Networks with Different Time Delays

In this paper‎, ‎a bidirectional ring network with three cells and different time delays is presented‎. ‎To propose this model which is a good extension of three-unit neural networks‎, ‎coupled cell network theory and neural network theory are applied‎. ‎In this model‎, ‎every cell has self-connections without delay but different time delays are assumed in other connections‎. ‎A suitable Lyapun...

متن کامل

Robust Fault Detection on Boiler-turbine Unit Actuators Using Dynamic Neural Networks

Due to the important role of the boiler-turbine units in industries and electricity generation, it is important to diagnose different types of faults in different parts of boiler-turbine system. Different parts of a boiler-turbine system like the sensor or actuator or plant can be affected by various types of faults. In this paper, the effects of the occurrence of faults on the actuators are in...

متن کامل

PROJECTED DYNAMICAL SYSTEMS AND OPTIMIZATION PROBLEMS

We establish a relationship between general constrained pseudoconvex optimization problems and globally projected dynamical systems. A corresponding novel neural network model, which is globally convergent and stable in the sense of Lyapunov, is proposed. Both theoretical and numerical approaches are considered. Numerical simulations for three constrained nonlinear optimization problems a...

متن کامل

PREDICTION OF BIAXIAL BENDING BEHAVIOR OF STEEL-CONCRETE COMPOSITE BEAM-COLUMNS BY ARTIFICIAL NEURAL NETWORK

In this study, the complex behavior of steel encased reinforced concrete (SRC) composite beam–columns in biaxial bending is predicted by multilayer perceptron neural network. For this purpose, the previously proposed nonlinear analysis model, mixed beam-column formulation, is verified with biaxial bending test results. Then a large set of benchmark frames is provided and P-Mx-My triaxial ...

متن کامل

Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks

‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎Then‎, ‎we use...

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 2004