Synchronization control for Markov jump neural networks subject to HMM observation and partially known detection probabilities

作者：

Highlights：

• An hidden Markov model is used to avoid some imperfect hypotheses when handling the synchronization control issue for MJNNs.

• The HMM is with partial known detection probabilities, which can remedy the disadvantage of some previous works.

• Activation function dividing method is used to get less conservative result for the synchronization control issue for MJNNs.

摘要

•An hidden Markov model is used to avoid some imperfect hypotheses when handling the synchronization control issue for MJNNs.•The HMM is with partial known detection probabilities, which can remedy the disadvantage of some previous works.•Activation function dividing method is used to get less conservative result for the synchronization control issue for MJNNs.

论文关键词：Markov jump neural networks,Synchronization control,Hidden Markov model (HMM),Partial detection probabilities

论文评审过程：Received 28 August 2018, Revised 14 January 2019, Accepted 8 April 2019, Available online 22 May 2019, Version of Record 22 May 2019.

论文官网地址：https://doi.org/10.1016/j.amc.2019.04.032