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Brainmorphic Computing Hardware

update:2020-06-16
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We will develop a brainmorphic computing hardware, which realizes the brain-specific functions such as conscious/sub-conscious process, self, selective attention, and so on, by directly using inherent physics and dynamics of constituent devices. The resulting hardware would be small, efficient, high-performance. Some examples include the chaotic neural network reservoir, optimization through high-dimensional complex dynamics, and neural network composed of spin-orbit torque nano-devices.
The resulting hardware is suitable for the edge AI which learns users’ personal behavior. Examples include watching service devices embedded in hearing aids or dental implants, which monitor and learn personal cardiac and brain-wave signals or saliva ingredients, to detect abnormal situations.

Researchers

Research Institute of Electrical Communication

HORIO, Yoshihiko , Professor
Ph.D

Keywords

Related Information

[Papers]
Artificial neuron and synapse realized in an antiferromagnet/ferromagnet heterostructure using dynamics of spin-orbit torque switching [Advanced Materials, 1900636, 2019, DOI: 10.1002/adma.201900636]
A brainmorphic computing hardware paradigm through complex nonlinear dynamics [in Understanding Complex Systems, V. In, P. Longhini, and A. Palacios, eds., Springer, ISBN 978-3-030-10891-5, Chapter 5, pp. 36-43, 2019, DOI: 10.1007/987-3-030-10892-2_5]
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