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Stoliar, P.; Tranchant, J.; Corraze, B.; Janod, E.; Besland, M.-P.; Tesler, F.; Rozenberg, M.; Cario, L. "A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator" (2017) Advanced Functional Materials. 27(11)
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Abstract:

During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data-processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain-like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon-based circuits. However, so far, a single-component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two-terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow-gap Mott insulators subject to electric pulsing. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Registro:

Documento: Artículo
Título:A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
Autor:Stoliar, P.; Tranchant, J.; Corraze, B.; Janod, E.; Besland, M.-P.; Tesler, F.; Rozenberg, M.; Cario, L.
Filiación:CIC nanoGUNE, Tolosa Hiribidea 76, Donostia-San Sebastian, 20018, Spain
Institut des Matériaux Jean Rouxel (IMN), Université de Nantes, CNRS, 2 rue de la Houssinière, BP 32229, Nantes, Cedex 3 44322, France
Departamento de Física-IFIBA, FCEN, Universidad de Buenos Aires, Ciudad Universitaria Pabellón I, Buenos Aires, 1428, Argentina
Laboratoire de Physique des Solides, CNRS-UMR8502, Université de Paris-Sud, Orsay, 91405, France
Palabras clave:leaky integrate and fire; Mott insulators; neurons; Data handling; Data mining; High energy physics; Memristors; Neurons; Pattern recognition; Data processing applications; Integrate and fires; Leaky integrate and fire neuron; Mott insulators; Neumann architecture; Neuromorphic engineering; Silicon-based circuits; Two-terminal devices; Neural networks
Año:2017
Volumen:27
Número:11
DOI: http://dx.doi.org/10.1002/adfm.201604740
Título revista:Advanced Functional Materials
Título revista abreviado:Adv. Funct. Mater.
ISSN:1616301X
CODEN:AFMDC
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1616301X_v27_n11_p_Stoliar

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Citas:

---------- APA ----------
Stoliar, P., Tranchant, J., Corraze, B., Janod, E., Besland, M.-P., Tesler, F., Rozenberg, M.,..., Cario, L. (2017) . A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator. Advanced Functional Materials, 27(11).
http://dx.doi.org/10.1002/adfm.201604740
---------- CHICAGO ----------
Stoliar, P., Tranchant, J., Corraze, B., Janod, E., Besland, M.-P., Tesler, F., et al. "A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator" . Advanced Functional Materials 27, no. 11 (2017).
http://dx.doi.org/10.1002/adfm.201604740
---------- MLA ----------
Stoliar, P., Tranchant, J., Corraze, B., Janod, E., Besland, M.-P., Tesler, F., et al. "A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator" . Advanced Functional Materials, vol. 27, no. 11, 2017.
http://dx.doi.org/10.1002/adfm.201604740
---------- VANCOUVER ----------
Stoliar, P., Tranchant, J., Corraze, B., Janod, E., Besland, M.-P., Tesler, F., et al. A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator. Adv. Funct. Mater. 2017;27(11).
http://dx.doi.org/10.1002/adfm.201604740