Explaining the hovering stochastic oscillations in self-organized quasi-critical systems (2018)
- Authors:
- USP affiliated authors: KINOUCHI FILHO, OSAME - FFCLRP ; SILVA FILHO, ANTONIO CARLOS ROQUE DA - FFCLRP ; RODRIGUES, LUDMILA BROCHINI - IME
- Unidades: FFCLRP; IME
- Subjects: OSCILADORES; NEUROCIÊNCIAS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Juan-les-Pins
- Date published: 2018
- Source:
- Título: Abstracts
- Conference titles: International Conference on Mathematical Neuroscience (ICMNS)
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ABNT
KINOUCHI, Osame et al. Explaining the hovering stochastic oscillations in self-organized quasi-critical systems. 2018, Anais.. Juan-les-Pins: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2018. . Acesso em: 29 dez. 2025. -
APA
Kinouchi, O., Brochini, L., Stolfi, J., Costa, A. de A., Roque, A. C., & Copelli, M. (2018). Explaining the hovering stochastic oscillations in self-organized quasi-critical systems. In Abstracts. Juan-les-Pins: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. -
NLM
Kinouchi O, Brochini L, Stolfi J, Costa A de A, Roque AC, Copelli M. Explaining the hovering stochastic oscillations in self-organized quasi-critical systems. Abstracts. 2018 ;[citado 2025 dez. 29 ] -
Vancouver
Kinouchi O, Brochini L, Stolfi J, Costa A de A, Roque AC, Copelli M. Explaining the hovering stochastic oscillations in self-organized quasi-critical systems. Abstracts. 2018 ;[citado 2025 dez. 29 ] - Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems
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- Response of electrically coupled Hodgkin-dimensional lattice
- Dynamical neuronal gains produce self-organized criticality in stochastic spiking neural networks
- Applications of a stochastic spiking neuron model to neural network modeling
- Signal compression in the sensory periphery
- Latin American School on Computational Neurosciene (LASCON), 3
- Perspective on applications of a stochastic spiking neuron model to neural network modeling
- Dynamical neuronal gains produce self-organized criticality in stochastic spiking neural networks
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