Rahimi, Mostafa, Giacomo, Indiveri, and Abbott, Derek (2014) Neuromorphic engineering: neuromimetic computation for understanding the brain. IEEE Life Sciences, June 2014.

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Abstract

Neuromorphic engineering attempts to understand the computational properties of neural processing systems by building electronic circuits and systems that emulate the principles of computation in the neural systems. The electronic systems that are developed in this process can serve both engineering and life sciences in various ways ranging from low-power brain-like computing embedded systems to neural-based control, brain machine interfaces, and neuroprosthesis. To realize such systems, various approaches and strategies with their own advantages and limitations, may be adopted. Here, we provide a summary of our recent article published in the proceedings of the IEEE [1], where we have discussed and reviewed the various approaches to the design and implementation of neuromorphic learning systems, and pointed out challenges and opportunities in these systems.

Item ID:	45728
Item Type:	Article (Short Note)
Date Deposited:	13 Jan 2017 02:30
FoR Codes:	09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090604 Microelectronics and Integrated Circuits @ 70% 10 TECHNOLOGY > 1007 Nanotechnology > 100705 Nanoelectronics @ 30%
SEO Codes:	97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 50% 97 EXPANDING KNOWLEDGE > 970110 Expanding Knowledge in Technology @ 50%
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