Oscillations in continuous-time ring neural network models with and without delay (1996)
- Authors:
- USP affiliated authors: MALTA, CORACI PEREIRA - IF ; RAGAZZO, CLODOALDO GROTTA - IME
- Unidades: IF; IME
- Assunto: FÍSICA MATEMÁTICA
- Language: Inglês
- Imprenta:
-
ABNT
MALTA, Coraci Pereira et al. Oscillations in continuous-time ring neural network models with and without delay. . São Paulo: IfUSP. Disponível em: http://publica-sbi.if.usp.br/PDFs/pd1202.pdf. Acesso em: 29 jan. 2026. , 1996 -
APA
Malta, C. P., Pakdaman, K., Vibert, J. F., Arino, O., & Ragazzo, C. G. (1996). Oscillations in continuous-time ring neural network models with and without delay. São Paulo: IfUSP. Recuperado de http://publica-sbi.if.usp.br/PDFs/pd1202.pdf -
NLM
Malta CP, Pakdaman K, Vibert JF, Arino O, Ragazzo CG. Oscillations in continuous-time ring neural network models with and without delay [Internet]. 1996 ;[citado 2026 jan. 29 ] Available from: http://publica-sbi.if.usp.br/PDFs/pd1202.pdf -
Vancouver
Malta CP, Pakdaman K, Vibert JF, Arino O, Ragazzo CG. Oscillations in continuous-time ring neural network models with and without delay [Internet]. 1996 ;[citado 2026 jan. 29 ] Available from: http://publica-sbi.if.usp.br/PDFs/pd1202.pdf - Effect of delay on the boundary of the basin of attraction in a system of two neurons
- "Asymptotic behavior of irreducible excitatory networks of analog graded-response neurons
- Bifurcation structure of scalar differential delayed equations
- Singularity structure of the hopf bifurcation surface of a differential equation with two delays
- Bifurcation structure of scalar differential delayed equations
- Effect of delay on the boundary of the basin of attraction in a self-excited single graded-response neuron
- Transition layer equations for positive-feedback delayed equations
- Single graded-response neuron model with recurrent excitation: distributed delay
- Asymptotic behavior of irreducible excitatory networks of graded-response neurons
- Non-existence of superexponential solutions in a system of delay differential equations modeling a two-neuron network
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