Exponential Stability for Delayed Cellular Neural Networks

• 作 者: 杨金祥 钟守铭 鄢克雨
• 机 构: College of Computer Science and Technology, Southwest University for Nationality Chengdu 610041 Chin
• 出 处: Journal of Electronic Science and Technology of China
• 发表日期: 2005年03期
• 关键词: exponentially exponential switching Liapunov have decomposed completed chips int

The exponential stability of the delayed cellular neural networks (DCNN’s) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. The new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.

The exponential stability of the delayed cellular neural networks (DCNN’s) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. the new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.