Novel bifurcation results for a delayed fractional-order quaternion-valued neural network

This paper reports the innovative results on the stability and bifurcation for a delayed fractional-order quaternion-valued neural network(FOQVNN). Delay-stimulated bifurcation criteria of the developed FOQVNN are attained. Then, the bifurcation diagrams are perfectly exhibited to authenticate the veracity of the bifurcation results. Besides, the stability zone is more larger of the addressed FOQVNN in comparison with its counterpart if other parameters are intercalated. It further witnesses that the amplitudes of bifurcation oscillation get bigger with the augmentation of time delay. It discloses that the bifurcation phenomena engender earlier as the order incrementally magnifies. The exactness and merits of the achieved analytic results are eventually substantiated by a simulation example. (C) 2019 Elsevier Ltd. All rights reserved.

本文报道了关于时滞分数阶四元数值神经网络（FOQVNN）的稳定性和分岔的创新结果。得到了所构建的FOQVNN的时滞激励分岔准则。然后，完美地展示了分岔图以验证分岔结果的准确性。此外，如果插入其他参数，所研究的FOQVNN的稳定区域比其同类网络更大。它还表明，随着时滞的增加，分岔振荡的幅度变大。它揭示了随着阶数逐渐增大，分岔现象更早出现。最后通过一个仿真例子证实了所获得的分析结果的准确性和优点。© 2019爱思唯尔有限公司。保留所有权利。