Bifurcations in a fractional-order neural network with multiple leakage delays

Neural Netw. 2020 Nov:131:115-126. doi: 10.1016/j.neunet.2020.07.015. Epub 2020 Jul 18.

Abstract

This paper expatiates the stability and bifurcation for a fractional-order neural network (FONN) with double leakage delays. Firstly, the characteristic equation of the developed FONN is circumspectly researched by employing inequable delays as bifurcation parameters. Simultaneously the bifurcation criteria are correspondingly extrapolated. Then, unequal delays-spurred-bifurcation diagrams are primarily delineated to confirm the precision and correctness for the values of bifurcation points. Furthermore, it lavishly illustrates from the evidence that the stability performance of the proposed FONN can be demolished with the presence of leakage delays in accordance with comparative studies. Eventually, two numerical examples are exploited to underpin the feasibility of the developed theory. The results derived in this paper have perfected the retrievable outcomes on bifurcations of FONNs embodying unique leakage delay, which can nicely serve a benchmark deliberation and provide a comparatively credible guidance for the influence of multiple leakage delays on bifurcations of FONNs.

Keywords: Fractional-order neural networks; Hopf bifurcation; Multiple leakage delays; Stability.

MeSH terms

  • Neural Networks, Computer*
  • Time