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In this paper, we give a complete analysis of the equilibrium points of background neural networks with uniform firing rates. By using continuity, monotonicity of some functions and Rolle’s theorem,… Click to show full abstract
In this paper, we give a complete analysis of the equilibrium points of background neural networks with uniform firing rates. By using continuity, monotonicity of some functions and Rolle’s theorem, the number of equilibrium points and their locations are obtained. Moreover, some novel sufficient conditions are given to guarantee the stability of the equilibrium points for the network model by utilizing Taylor’s theorem. A simulation example is conducted to illustrate the theories developed in this paper.
Keywords:
equilibrium points;
neural networks;
equilibrium;
points background;
analysis equilibrium;
background neural
Journal Title: Advances in Difference Equations
Year Published: 2017
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Journal Title: Advances in Difference Equations
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!