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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… Click to show full 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;
matrix based;
integral inequality;
based integral;
stability;
composite matrix
Journal Title: Mathematics
Year Published: 2023
Link to full text (if available)
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Journal Title: Mathematics
Year Published: 2023
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!