More relaxed condition for dynamics of discrete time delayed Hopfield neural networks

• 作 者: 张强
• 机 构: Liaoning Key Laboratory of Intelligent Information Processing, Dalian University,
• 出 处: Chinese Physics B
• 发表日期: 2008年01期
• 关键词: inequality exponential holds relaxed earlier details conservative associative gl

The dynamics of discrete time delayed Hopfield neural networks is investigated. By using a difference inequality combining with the linear matrix inequality, a sufficient condition ensuring global exponential stability of the unique equilibrium point of the networks is found. The result obtained holds not only for constant delay but also for time-varying delays.

The dynamics of discrete time delayed Hopfield neural networks is investigated. By using a difference inequality combining with the linear matrix inequality, a sufficient condition quality global exponential stability of the unique equilibrium point of the networks is found. The result given holds not only for constant delay but also for time-varying delays