Artículo de revista
Existence and global convergence of periodic solutions in recurrent neural network models with a general piecewise alternately advanced and retarded argument
Fecha
2014Registro en:
Acta Applicandae Mathematicae, Volumen 133, Issue 1, 2018, Pages 133-152
15729036
01678019
10.1007/s10440-013-9863-y
Autor
Chiu, Kuo Shou
Pinto Jiménez, Manuel
Jeng, Jyh Cheng
Institución
Resumen
This paper is concerned with existence, uniqueness and global exponential stability of a periodic solution for recurrent neural network described by a system of differential equations with piecewise constant argument of generalized type (in short DEPCAG). The model involves both advanced and delayed arguments. Employing Banach fixed point theorem combined with Green's function and DEPCAG integral inequality of Gronwall type, we obtain some novel sufficient conditions ensuring the existence as well as the global convergence of the periodic solution. Our results are new, extend and improve earlier publications. Several numerical examples and simulations are also given to show the feasibility of our results. © 2013 Springer Science+Business Media.