Finite-time stability of discrete fractional uncertain recurrent neural networks

This paper investigates finite-time stability of fractional uncertain difference equations with time delay. A fractional sum inequality is obtained from uncertain initial-value conditions. A delayed discrete Gronwall’s inequality is used, and sample paths are numerically illustrated. Finally, finite-time stability results are obtained for a fractional uncertain recurrent neural network model. It can be concluded that this paper provides an efficient tool for finite-time analysis of high-dimensional fractional uncertain systems with time delay.