Quasi-projective synchronization analysis of discrete-time FOCVNNs via delay-feedback control

Abstract

In this article, the quasi-projective synchronization (QPS) issues about discrete-time fractional-order complex-valued neural networks (DFOCVNNs) are discussed. To realize QPS, the delay-feedback controllers are designed. The main advantage of this controller is that it can search for control gain parameters over a wider range. Applying inequality techniques, Lyapunov method and some lemmas related to discrete fractional calculus, some criteria for QPS are inferred. Meanwhile, the error bound is effectively estimated. Eventually, we display two examples to verify the obtained criteria.