Global Exponential Stability of Almost Periodic Solution for A Large Class of Delayed Dynamical Systems
Abstract
Research of delayed neural networks with variable self-inhibitions, inter-connection weights, and inputs is an important issue. %In the real world, self-inhibitions, %inter-connection weights, and inputs should vary through time. In In this paper, we discuss a large class of delayed dynamical systems with almost periodic self-inhibitions, inter-connection weights, and inputs. This model is universal and includes delayed systems with time-varying delays, distributed delays as well as combination of both. We prove that under some mild conditions, the system has a unique almost periodic solution, which is globally exponentially stable. We propose a new approach, which is independent of existing theory concerning with existence of almost periodic solution for dynamical systems.
Keywords
Cite
@article{arxiv.math/0610920,
title = {Global Exponential Stability of Almost Periodic Solution for A Large Class of Delayed Dynamical Systems},
author = {Wenlian Lu and Tianping Chen},
journal= {arXiv preprint arXiv:math/0610920},
year = {2007}
}