Stability and Hopf-bifurcating periodic solution for delayed Hopfield neural networks with \(n\) neuron
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Publication:2336602
DOI10.1155/2014/628637zbMath1442.34115OpenAlexW2079131099WikidataQ59053861 ScholiaQ59053861MaRDI QIDQ2336602
Haji Mohammad Mohammadinejad, Mohammad Hadi Moslehi
Publication date: 19 November 2019
Published in: Journal of Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2014/628637
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Cites Work
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- Bifurcations, stability, and monotonicity properties of a delayed neural network model
- Temporal dynamics of a two-neuron continuous network model with time delay
- Globally exponential stability conditions for cellular neural networks with time-varying delays.
- Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays
- Stability, bifurcation and global existence of a Hopf-bifurcating periodic solution for a class of three-neuron delayed network models
- HIDDEN ATTRACTORS IN DYNAMICAL SYSTEMS. FROM HIDDEN OSCILLATIONS IN HILBERT–KOLMOGOROV, AIZERMAN, AND KALMAN PROBLEMS TO HIDDEN CHAOTIC ATTRACTOR IN CHUA CIRCUITS
- Global exponential stability of Hopfield neural networks
- Neurons with graded response have collective computational properties like those of two-state neurons.
- Estimation on domain of attraction and convergence rate of Hopfield continuous feedback neural networks