EXPONENTIAL STABILITY OF BAM-TYPE NEURAL NETWORKS WITH CONFORMABLE DERIVATIVE.

This paper investigates the fractional exponential stability of bidirectional associative memory (BAM) neural networks with conformable derivative. Applying the contraction mapping theorem existence and uniqueness of the equilibrium is studied. Furthermore, an appropriate Lyapunov function is stated to get exponential stability. Numerical examples are given to illustrate the obtained results. [ABSTRACT FROM AUTHOR]