Global Hopf bifurcation analysis of a BAM neural network with delays

DOI10.1016/j.mcm.2006.04.005zbMath1151.34060OpenAlexW1971436314MaRDI QIDQ2471605

Chengjun Sun, Mao'an Han

Publication date: 22 February 2008

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2006.04.005

zbMATH Keywords

neural networkmultiple periodic solutionsglobal Hopf bifurcationadditive compound matrixBendixson's criterion

Mathematics Subject Classification ID

Transformation and reduction of functional-differential equations and systems, normal forms (34K17) Stability theory of functional-differential equations (34K20) Linear functional-differential equations (34K06) Periodic solutions to functional-differential equations (34K13) Bifurcation theory of functional-differential equations (34K18)

Related Items (7)

AN EFFICIENT METHOD FOR STUDYING FOLD-HOPF BIFURCATION IN DELAYED NEURAL NETWORKS ⋮ Existence and stability analysis of bifurcating periodic solutions in a delayed five-neuron BAM neural network model ⋮ Bifurcation analysis for a tri-neuron discrete-time BAM neural network with delays ⋮ Global dynamics of delayed intraguild predation model with intraspecific competition ⋮ Bautin bifurcation in a class of two-neuron networks with resonant bilinear terms ⋮ Stability and global Hopf bifurcation analysis on a ratio-dependent predator-prey model with two time delays ⋮ Fold-Hopf bifurcation in a simplified four-neuron BAM (bidirectional associative memory) neural network with two delays

Cites Work

• On Bendixson's criterion
• On a planar system modelling a neuron network with memory
• Stability and Hopf bifurcation analysis on a simplified BAM neural network with delays
• Stability and bifurcation in a neural network model with two delays.
• Delay induced periodicity in a neural netlet of excitation and inhibition
• Compound matrices and ordinary differential equations
• Symmetric functional differential equations and neural networks with memory
• Neurons with graded response have collective computational properties like those of two-state neurons.
• Global exponential stability in continuous-time and discrete-time delayed bidirectional neural networks

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