Neuromorphic computing's yesterday, today, and tomorrow – an evolutional view
Neuromorphic computing was originally referred to as the hardware that mimics neuro-biological architectures to implement models of neural systems. The concept was then extended to the computing systems that can run bio-inspired computing models, e.g., neural networks and deep learning networks. In recent years, the rapid growth of cognitive applications and the limited processing capability of conventional von Neumann architecture on these applications motivated worldwide research on neuromorphic computing systems. In this paper, we review the evolution of neuromorphic computing technique in both computing model and hardware implementation from a historical perspective. Various implementation methods and practices are also discussed. Finally, we present some emerging technologies that may potentially change the landscape of neuromorphic computing in the future, e.g., new devices and interdisciplinary computing architectures.
Duke Scholars
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- Computer Hardware & Architecture
- 4009 Electronics, sensors and digital hardware
- 1006 Computer Hardware
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Published In
DOI
ISSN
Publication Date
Volume
Start / End Page
Related Subject Headings
- Computer Hardware & Architecture
- 4009 Electronics, sensors and digital hardware
- 1006 Computer Hardware