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Your search keyword '"Kei Ashiba"' showing total 2 results
Start Over Author "Kei Ashiba" Journal frontiers in neuroscience
2 results on '"Kei Ashiba"'

1. Double MgO-Based Perpendicular Magnetic Tunnel Junction for Artificial Neuron

Author

Dong Won Kim, Woo Seok Yi, Jin Young Choi, Kei Ashiba, Jong Ung Baek, Han Sol Jun, Jae Joon Kim, and Jea Gun Park

Subjects
neuromorphic, MRAM, spiking neuron, spiking neural network, artificial neuron, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

A perpendicular spin transfer torque (p-STT)-based neuron was developed for a spiking neural network (SNN). It demonstrated the integration behavior of a typical neuron in an SNN; in particular, the integration behavior corresponding to magnetic resistance change gradually increased with the input spike number. This behavior occurred when the spin electron directions between double Co2Fe6B2 free and pinned layers in the p-STT-based neuron were switched from parallel to antiparallel states. In addition, a neuron circuit for integrate-and-fire operation was proposed. Finally, pattern-recognition simulation was performed for a single-layer SNN.

Published
2020
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2. Double MgO-Based Perpendicular Magnetic Tunnel Junction for Artificial Neuron

Author

Kei Ashiba, Woo Seok Yi, Jea-Gun Park, Jong Ung Baek, Han Sol Jun, Jin Young Choi, Jae-Joon Kim, and Dong Won Kim

Subjects
Materials science, artificial neuron, neuromorphic, 02 engineering and technology, Electron, Topology, lcsh:RC321-571, spiking neural network, 03 medical and health sciences, Neuron circuit, Artificial neuron, Perpendicular, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Original Research, 030304 developmental biology, Spiking neural network, 0303 health sciences, Magnetoresistive random-access memory, Quantitative Biology::Neurons and Cognition, spiking neuron, General Neuroscience, MRAM, 021001 nanoscience & nanotechnology, Tunnel magnetoresistance, Neuromorphic engineering, 0210 nano-technology, Neuroscience
Abstract

A perpendicular spin transfer torque (p-STT)-based neuron was developed for a spiking neural network (SNN). It demonstrated the integration behavior of a typical neuron in an SNN; in particular, the integration behavior corresponding to magnetic resistance change gradually increased with the input spike number. This behavior occurred when the spin electron directions between double Co2Fe6B2 free and pinned layers in the p-STT-based neuron were switched from parallel to antiparallel states. In addition, a neuron circuit for integrate-and-fire operation was proposed. Finally, pattern-recognition simulation was performed for a single-layer SNN.

Published
2020

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