Global stabilization of fractional-order bidirectional associative memory neural networks with mixed time delays via adaptive feedback control

Abstract

This paper focuses on the stabilization problem for a class of fractional-order bidirectional associative memory neural networks with mixed time delays (discrete delay and finite-time distributed delay). Based on adaptive control and delay feedback control, two kinds of adaptive control schemes are proposed to realize the global stabilization of systems. Different from those in earlier works, our method mainly depends on two fractional inequalities and a new fractional-order Barbalat lemma. Finally, some numerical simulations are provided to illustrate the feasibility and effectiveness of the proposed adaptive control schemes.

Keywords:

• Fractional-order system
• bidirectional associative memory neural networks
• stabilization
• adaptive control
• fractional-order Barbalat's lemma

2010 Mathematics Subject Classifications:

• 34D23
• 93C15
• 93C40

Acknowledgments

The authors would like to express their sincere gratitude to several anonymous referees for their valuable comments and suggestions on this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by the National Natural Science Foundation of China (grant number 11401595).