A canonical model for gradient frequency neural networks
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Publication:979098
DOI10.1016/j.physd.2009.11.015zbMath1189.37061OpenAlexW2012109990MaRDI QIDQ979098
Felix V. Almonte, Marc J. Velasco, Edward W. Large
Publication date: 25 June 2010
Published in: Physica D (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physd.2009.11.015
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Cites Work
- Unnamed Item
- Unnamed Item
- Hypernormal form theory: foundations and algorithms
- Amplitude response of coupled oscillators
- Weakly connected neural networks
- Normal form theory and spectral sequences.
- Further reductions of normal forms for dynamical systems
- On the relation between the methods of averaging and normal forms
- Synaptic organizations and dynamical properties of weakly connected neural oscillators. I: Analysis of a canonical model
- A RECURSIVE APPROACH TO COMPUTE NORMAL FORMS
- A perturbation method for computing the simplest normal forms of dynamical systems
- Free vibration and buckling of shear-deformable cross-ply laminated plates using the state-space concept
- A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue
- Normal Forms and Unfoldings for Local Dynamical Systems
- HIGHER ORDER NORMAL FORM AND PERIOD AVERAGING
- SIMPLEST NORMAL FORMS OF HOPF AND GENERALIZED HOPF BIFURCATIONS
- Higher Order Averaging and Related Methods for Perturbed Periodic and Quasi-Periodic Systems
- Elements of applied bifurcation theory
