AdaptHD - Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing

Mohsen Imani
Mohsen Imani
Justin Morris
Justin Morris
Samuel Bosch
Samuel Bosch
Helen Shu
Helen Shu
Giovanni De Micheli
Giovanni De Micheli

BioCAS, pp. 1-4, 2019.

Cited by: 0|Views28
EI

Abstract:

Brain-inspired Hyperdimensional (HD) computing is a promising solution for energy-efficient classification. HD emulates cognition tasks by exploiting long-size vectors instead of working with numeric values used in contemporary processors. However, the existing HD computing algorithms have lack of controllability on the training iteration...More

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