Exponential p-convergence analysis for stochastic BAM neural networks with time-varying and infinite distributed delays
作者：
Highlights：
• We discuss exponential p-convergence for stochastic BAM neural networks.
• The delays here are multiple time-varying and infinite distributed delays.
• We establish a new L-operator delay differential-integral inequality.
• Delay-dependent criteria ensuring exponential p-convergence are obtained.
• Giving the detail estimations of the exponential p-convergence ball.
摘要
•We discuss exponential p-convergence for stochastic BAM neural networks.•The delays here are multiple time-varying and infinite distributed delays.•We establish a new L-operator delay differential-integral inequality.•Delay-dependent criteria ensuring exponential p-convergence are obtained.•Giving the detail estimations of the exponential p-convergence ball.
论文关键词：Stochastic BAM neural networks,Exponential p-convergence,Infinite distributed delays,L-operator differential-integral inequality,Ito^’s formula
论文评审过程：Received 17 January 2015, Revised 5 April 2015, Accepted 2 June 2015, Available online 25 June 2015, Version of Record 25 June 2015.
论文官网地址：https://doi.org/10.1016/j.amc.2015.06.022
