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AIMS Mathematics

2024, Volume 9, Issue 7: 19049-19067. doi: 10.3934/math.2024927
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Research article

A novel nonzero functional method to extended dissipativity analysis for neural networks with Markovian jumps

  • 1.
    Internet of Things Department, Henan Institute of Economics and Trade, Zhengzhou 450000, China
  • 2.
    College of Automation, Chongqing University, 400044, China
  • 3.
    School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore
  • 4.
    College of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China
  • Received: 26 March 2024 Revised: 26 May 2024 Accepted: 03 June 2024 Published: 06 June 2024

  • MSC : 37C75, 93C55, 92B20

  • This paper explored the topic of extended dissipativity analysis for Markovian jump neural networks (MJNNs) that were influenced by time-varying delays. A distinctive Lyapunov functional, distinguished by a non-zero delay-product types, was presented. This was achieved by combining a Wirtinger-based double integral inequality with a flexible matrix set. This novel methodology addressed the limitations of the slack matrices found in earlier research. As a result, a fresh condition for extended dissipativity in MJNNs was formulated, utilizing an exponential type reciprocally convex inequality in conjunction with the newly introduced nonzero delay-product types. A numerical example was included to demonstrate the effectiveness of the proposed methodology.

    Citation: Wenlong Xue, Yufeng Tian, Zhenghong Jin. A novel nonzero functional method to extended dissipativity analysis for neural networks with Markovian jumps[J]. AIMS Mathematics, 2024, 9(7): 19049-19067. doi: 10.3934/math.2024927

    Related Papers:

  • This paper explored the topic of extended dissipativity analysis for Markovian jump neural networks (MJNNs) that were influenced by time-varying delays. A distinctive Lyapunov functional, distinguished by a non-zero delay-product types, was presented. This was achieved by combining a Wirtinger-based double integral inequality with a flexible matrix set. This novel methodology addressed the limitations of the slack matrices found in earlier research. As a result, a fresh condition for extended dissipativity in MJNNs was formulated, utilizing an exponential type reciprocally convex inequality in conjunction with the newly introduced nonzero delay-product types. A numerical example was included to demonstrate the effectiveness of the proposed methodology.


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