Some improved methods to analysis stability of recurrent neural networks with interval time-varying delays

ABSTRACT

This paper considers the delay-dependent stability problem of recurrent neural networks with interval time-varying delays. An appropriate Lyapunov–Krasovskii functional is constructed and the combination method of Wirtinger inequality and reciprocally convex optimization technique is employed. Combing a new activation function segmentation method of the boundary condition and the orthogonal complement lemma, three further improved delay-dependent stability criteria are established. Finally, two numerical examples show the effectiveness of our proposed method by comparison with the recent existing works.

KEYWORDS:

• Recurrent neural networks
• LKF
• interval time-varying delays
• stability criteria

AMS SUBJECT CLASSIFICATIONS:

• 34D05
• 34D20
• 34K10
• 34K20

Disclosure statement

No potential conflict of interest was reported by the authors.