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

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