Neuron and neuromorphic system including the same
AssigneeIndustry-University Cooperation Foundation Hanyang University
InventorsJea Gun Park, Dong Won Kim
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Abstract
The present invention discloses a neuron and a neuromorphic system including the same. The neuron according to an embodiment of the present invention includes a metal insulator metal (MIM) device including a metal ion-doped insulating layer and configured to perform integration and fire, and the MIM device is formed to have a negative differential resistance (NDR) region in which current decreases as voltage increases.
Claims13
A neuron, comprising a metal insulator metal (MIM) device comprising a metal ion-doped insulating layer and configured to perform integration and fire,
- wherein the MIM device comprising the metal ion-doped insulating layer is formed to have a negative differential resistance (NDR) region in which current decreases as voltage increases,
- wherein the metal ion-doped insulating layer comprises a plurality of metal vacancies which form a plurality of metal bridges in the metal ion-doped insulating layer,
- wherein the plurality of metal bridges are formed to have at least one thickness based on a number of the plurality of metal vacancies to create at least one of a high-resistance state or a low resistance state by at least one of an applied set voltage or a reset voltage, the at least one thickness comprising a first thickness and a second thickness wider than the first thickness,
- wherein, based on the high-resistance state, the plurality of metal bridges are formed to the first thickness, the first thickness being configured to be broken,
- wherein, based on the low-resistance state, the plurality of metal bridges are formed to the second thickness,
- wherein the integration is a process in which an electrical signal (input spikes) input through one or more synapses is integrated in a form of a potential,
- wherein the fire is a process in which the accumulated potential reaches a first threshold and an electrical signal (output spikes) is output to adjacent neurons, and
- wherein the MIM device comprising the metal ion-doped insulating layer performs the integration, and performs the fire when resistance reaches a threshold resistance (Rth) selected according to a predetermined precision and a predetermined reproducibility of a neural network composed of the neuron and the adjacent neurons.
A neuromorphic system, comprising:
- one or more pre-neurons;
- one or more synapses electrically connected to the one or more pre-neurons;
- and
- one or more post-neurons electrically connected to the one or more synapses and each comprising a metal insulator metal (MIM) device comprising a metal ion-doped insulating layer,
- wherein the one or more post-neurons perform integration and fire,
- wherein the metal ion-doped insulating layer comprises a plurality of metal vacancies which form a plurality of metal bridges in the metal ion-doped insulating layer,
- wherein the plurality of metal bridges are formed to have at least one thickness based on a number of the plurality of metal vacancies to create at least one of a high-resistance state or a low resistance state by at least one of an applied set voltage or a reset voltage, the at least one thickness comprising a first thickness and a second thickness wider than the first thickness,
- wherein, based on the high-resistance state, the plurality of metal bridges are formed to the first thickness, the first thickness being configured to be broken,
- wherein, based on the low-resistance state, the plurality of metal bridges are formed to the second thickness,
- wherein the integration is a process in which an electrical signal (input spikes) input through the one or more synapses is integrated in a form of a potential,
- wherein the fire is a process in which the accumulated potential reaches a first threshold and an electrical signal (output spikes) is output to adjacent neurons,
- wherein the MIM device comprising the metal ion-doped insulating layer performs the integration, and performs the fire when resistance reaches a threshold resistance (Rth) selected according to a predetermined precision and a predetermined reproducibility of a neural network composed of the neuron and the adjacent neurons.
Dependencies are inferred from the claim text.