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Nonlinear Dynamics

, Volume 92, Issue 4, pp 1583–1598 | Cite as

Stability analysis for neutral-type inertial BAM neural networks with time-varying delays

  • Fengyan Zhou
  • Hongxing Yao
Original Paper
  • 212 Downloads

Abstract

The global asymptotic stability for neutral-type inertial BAM neural networks with time-varying delays is considered. By using variable transforming, homeomorphism theory, suitable Lyapunov functional together with matrix equations, some delay-dependent sufficient conditions are established to ascertain the existence and global asymptotic stability of this neutral-type inertial BAM neural networks. All the conditions are obtained relying on linear matrix inequalities. Finally, two numerical examples are presented to illustrate the validity of theoretical results.

Keywords

Inertial neutral-type BAM neural networks Matrix equations Homeomorphism theory Lyapunov functional Asymptotic stability Time-varying delays 

Notes

Acknowledgements

The work is supported by the National Natural Science Foundation of China (Nos. 71701082, 71271103) and the Innovative Foundation for Doctoral Candidate of Jiangsu Province, China (Grant No. CXZZ13_0687).

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of ScienceJiangsu UniversityZhenjiangPeople’s Republic of China
  2. 2.Department of MathematicsShaoxing UniversityShaoxingPeople’s Republic of China
  3. 3.School of Finance and EconomicsJiangsu UniversityZhenjiangPeople’s Republic of China

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