Almost Periodic Dynamics of a Class of Delayed Neural Networks with Discontinuous Activations

Author:

Lu Wenlian1,Chen Tianping2

Affiliation:

1. Laboratory of Mathematics for Nonlinear Sciences, School of Mathematical Sciences, Fudan University, 200433, Shanghai, P.R.C., and Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany.

2. Laboratory of Mathematics for Nonlinear Sciences, School of Mathematical Sciences, Fudan University, 200433, Shanghai, P.R.C.

Abstract

We use the concept of the Filippov solution to study the dynamics of a class of delayed dynamical systems with discontinuous right-hand side, which contains the widely studied delayed neural network models with almost periodic self-inhibitions, interconnection weights, and external inputs. We prove that diagonal-dominant conditions can guarantee the existence and uniqueness of an almost periodic solution, as well as its global exponential stability. As special cases, we derive a series of results on the dynamics of delayed dynamical systems with discontinuous activations and periodic coefficients or constant coefficients, respectively. From the proof of the existence and uniqueness of the solution, we prove that the solution of a delayed dynamical system with high-slope activations approximates to the Filippov solution of the dynamical system with discontinuous activations.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

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