Stability Analysis of Delayed Neural Networks via Composite-Matrix-Based Integral Inequality

Yupeng Shi and Dayong Ye ()
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Yupeng Shi: College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Dayong Ye: School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China

Mathematics, 2023, vol. 11, issue 11, 1-13

Abstract: This paper revisits the problem of stability analyses for neural networks with time-varying delay. A composite-matrix-based integral inequality (CMBII) is presented, which takes the delay derivative into account. In this case, the coupling information can be fully captured in integral inequalities with the delay derivative. Based on a CMBII, a new stability criterion is derived for neural networks with time-varying delay. The effectiveness of this method is verified by a numerical example.

Keywords: neural networks; time-varying delay; stability analysis; integral inequality; delay derivative (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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