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Controller Design for Neutral Networks with Markov Jumps and a New Method for Exponential Stability Analysis

  • Deyong Ning*
  • , Hongqian Lu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study examines neutral neural network systems with Markov jump (MJNNNs)' mean square exponential stability. When discussing the stochastic catastrophe problem in complicated systems, Markov jump is crucial. First, a simple Lyapunov Krasovskii functional (LKF) containing sufficient system information is established, the GFWM-based inequality and other integral inequalities, a movable parameter, and enough random vectors are then used to calculate a single integral term in the derivative of the built LKF.

Original languageEnglish
Title of host publicationProceedings of the 36th Chinese Control and Decision Conference, CCDC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5196-5200
Number of pages5
ISBN (Electronic)9798350387780
DOIs
StatePublished - 2024
Externally publishedYes
Event36th Chinese Control and Decision Conference, CCDC 2024 - Xi'an, China
Duration: 25 May 202427 May 2024

Publication series

NameProceedings of the 36th Chinese Control and Decision Conference, CCDC 2024

Conference

Conference36th Chinese Control and Decision Conference, CCDC 2024
Country/TerritoryChina
CityXi'an
Period25/05/2427/05/24

Keywords

  • Controller design
  • GWFM-based inequality
  • Markov jump
  • Neutral neural network
  • Stable mean square index

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