A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator

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 an...

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Detalles Bibliográficos
Autor principal: Rozenberg, Marcelo Javier
Publicado: 2017
Materias:
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
Neumann architecture
Neuromorphic engineering
Silicon-based circuits
Two-terminal devices
Neural networks
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1616301X_v27_n11_p_Stoliar
http://hdl.handle.net/20.500.12110/paper_1616301X_v27_n11_p_Stoliar
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_1616301X_v27_n11_p_Stoliar
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spelling paper:paper_1616301X_v27_n11_p_Stoliar2025-07-30T19:01:04Z A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator Rozenberg, Marcelo Javier 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 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 Fil:Rozenberg, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2017 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1616301X_v27_n11_p_Stoliar http://hdl.handle.net/20.500.12110/paper_1616301X_v27_n11_p_Stoliar
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic 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
spellingShingle 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
Rozenberg, Marcelo Javier
A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
topic_facet 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
description 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
author Rozenberg, Marcelo Javier
author_facet Rozenberg, Marcelo Javier
author_sort Rozenberg, Marcelo Javier
title A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_short A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_full A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_fullStr A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_full_unstemmed A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_sort leaky-integrate-and-fire neuron analog realized with a mott insulator
publishDate 2017
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1616301X_v27_n11_p_Stoliar
http://hdl.handle.net/20.500.12110/paper_1616301X_v27_n11_p_Stoliar
work_keys_str_mv AT rozenbergmarcelojavier aleakyintegrateandfireneuronanalogrealizedwithamottinsulator
AT rozenbergmarcelojavier leakyintegrateandfireneuronanalogrealizedwithamottinsulator
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