Suppr超能文献

具有非光滑和冲击激活的神经网络的全局指数稳定性。

Global exponential stability of neural networks with non-smooth and impact activations.

机构信息

Department of Mathematics, Middle East Technical University, 06531 Ankara, Turkey.

出版信息

Neural Netw. 2012 Oct;34:18-27. doi: 10.1016/j.neunet.2012.06.004. Epub 2012 Jun 26.

Abstract

In this paper, we consider a model of impulsive recurrent neural networks with piecewise constant argument. The dynamics are presented by differential equations with discontinuities such as impulses at fixed moments and piecewise constant argument of generalized type. Sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are obtained. By employing Green's function we derive new result of existence of the periodic solution. The global exponential stability of the solution is investigated. Examples with numerical simulations are given to validate the theoretical results.

摘要

本文考虑了具有分段常数自变量的脉冲递归神经网络模型。动力系统由具有不连续项的微分方程表示,如在固定时刻的脉冲和广义分段常数自变量。得到了保证平衡点存在、唯一性和全局指数稳定性的充分条件。通过使用格林函数,我们得到了周期解存在的新结果。研究了解的全局指数稳定性。通过数值模拟给出了实例,验证了理论结果。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验