Reachable set bounding for a class of bidirectional associative memory NNSs with Markov jump switching parameters

  • Zhang He
  • Junwei Lu
  • Yunliang Wei
  • Yuming Chu


This paper studies the problem how to estimate the reachable set for a class of delayed bidirectional associative memory neural network systems (NNSs), which have Markov switching parameters and unit-energy or unit-peak bounded disturbance inputs. The feature of the Markov jump bidirectional associative memory NNSs shows in the following twofold: the time delay is time varying; the transition rates is time varying. Moreover, the time-varying transition rates is piecewise constant. Using the Lyapunov functional method, delay-partitioning and linear matrix inequalities techniques, the estimate problem of the reachable set depending on time delay is solved. The effectiveness of the given results is illustrated by the proposed numerical examples.


Markov jump Reachable set estimation Bidirectional associative memory NNSs Piecewise-constant transition rates Time delay 

Mathematics Subject Classification

00-01 99-00 



This work was supported in part supported by both the National Natural Science Foundation of China under Grants 11401062 and 61374104, NSFC 61374086, the Natural Science Foundation of Jiangsu Province under Grant BK20140770, BK20131097. The authors would like to express sincere appreciation to the editor and anonymous reviewers for their valuable comments which have led to an improvement in the presentation of the paper.


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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2018

Authors and Affiliations

  1. 1.School of AutomationNanjing University of Science and TechnologyNanjingChina
  2. 2.School of Electrical and Automation EngineeringNanjing Normal UniversityNanjingChina
  3. 3.School of Mathematical SciencesQufu Normal UniversityQufuChina
  4. 4.School of ScienceHuzhou Teachers CollegeHuzhouChina

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