Disparate delays-induced bifurcations in a fractional-order neural network

The problem of bifurcation for delayed fractional neural networks(FNNs) with single delay has been considerably researched. It is more realistic to portray the dynamical properties of FNNs with multiple delays, but this has been not investigated before. This paper attempts to conduct a research on the stability and bifurcation for a FNN with double delays. The criteria of heterogeneous delays-induced bifurcations are decidedly procured. Then, the influence of solitary delay on the bifurcation point is ulteriorly displayed by delicate computation. It is demonstrated that the stability performance of the proposed FNN can be undermined or enhanced by varying properly time delay. Finally, illustrative examples are addressed to validate the availability of the proposed results. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.