Exploration of bifurcation for a fractional-order BAM neural network with n+2 neurons and mixed time delays. (June 2022)
- Record Type:
- Journal Article
- Title:
- Exploration of bifurcation for a fractional-order BAM neural network with n+2 neurons and mixed time delays. (June 2022)
- Main Title:
- Exploration of bifurcation for a fractional-order BAM neural network with n+2 neurons and mixed time delays
- Authors:
- Wang, Yangling
Cao, Jinde
Huang, Chengdai - Abstract:
- Abstract: This article aims to deal with the stability and Hopf bifurcation analysis for a type of fractional-order bidirectional associative memory (BAM) neural network involving two neurons in the X -layer and n neurons in the Y -layer, respectively. In view of the universal existence and multiplicity of time delay in many real systems, leakage delay and nonuniform communication delays are both taken into account. Coates's flow-graph formula is efficiently adopted to solve the high-order characteristic equation of the associated linearized system. By making some assumptions on the mixed time delays, the obtained characteristic equation only contains the leakage delay, which is selected as the bifurcation parameter. Utilizing the discriminated criteria of stability for fractional-order dynamical systems and Hopf bifurcation theory, we obtain the critical value of the bifurcation point, greater than which the Hopf bifurcation would occur. Particularly, the stability and Hopf bifurcation is also analyzed for the case of no leakage delay to get an insight into the effect of the leakage delay. Finally, the validity of our theoretical results is substantiated through a simulation example. Highlights: A generalized fractional delayed ( n + 2)-neuron BAM neural network is proposed. Signal flow-graph theory is efficiently used to solve the characteristic equation. Some novel criteria of stability and Hopf bifurcation are given. The effect of the leakage delay on Hopf bifurcation isAbstract: This article aims to deal with the stability and Hopf bifurcation analysis for a type of fractional-order bidirectional associative memory (BAM) neural network involving two neurons in the X -layer and n neurons in the Y -layer, respectively. In view of the universal existence and multiplicity of time delay in many real systems, leakage delay and nonuniform communication delays are both taken into account. Coates's flow-graph formula is efficiently adopted to solve the high-order characteristic equation of the associated linearized system. By making some assumptions on the mixed time delays, the obtained characteristic equation only contains the leakage delay, which is selected as the bifurcation parameter. Utilizing the discriminated criteria of stability for fractional-order dynamical systems and Hopf bifurcation theory, we obtain the critical value of the bifurcation point, greater than which the Hopf bifurcation would occur. Particularly, the stability and Hopf bifurcation is also analyzed for the case of no leakage delay to get an insight into the effect of the leakage delay. Finally, the validity of our theoretical results is substantiated through a simulation example. Highlights: A generalized fractional delayed ( n + 2)-neuron BAM neural network is proposed. Signal flow-graph theory is efficiently used to solve the characteristic equation. Some novel criteria of stability and Hopf bifurcation are given. The effect of the leakage delay on Hopf bifurcation is deeply discussed. A simulation example is given to validate the presented theoretical results. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 159(2022)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 159(2022)
- Issue Display:
- Volume 159, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 159
- Issue:
- 2022
- Issue Sort Value:
- 2022-0159-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06
- Subjects:
- Hopf bifurcation -- Fractional-order BAM neural network -- n + 2 neurons -- Leakage delay -- Nonuniform communication delays
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2022.112117 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21561.xml