Programmable neuromorphic circuits for spike-based neural dynamics

Rahimi Azghadi, Mostafa, Moradi, Saber, and Indiveri, Giacomo (2013) Programmable neuromorphic circuits for spike-based neural dynamics. In: Proceedings of the 11th International New Circuits and Systems Conference. pp. 1-4. From: NEWCAS 2013: 11th International New Circuits and Systems Conference, 16-19 June 2013, Paris, France.

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Hardware implementations of spiking neural networks offer promising solutions for a wide set of tasks, ranging from autonomous robotics to brain machine interfaces. We propose a set of programmable hybrid analog/digital neuromorphic circuits than can be used to build compact low-power neural processing systems. In particular, we present both CMOS and hybrid memristor/CMOS synaptic circuits that have programmable synaptic weights and exhibit biologically plausible response properties. For the CMOS circuits, we present experimental results demonstrating that they operate correctly over a wide range input frequencies; for the hybrid memristor/CMOS circuits we present circuit simulation results validating their expected response properties.

Item ID: 45713
Item Type: Conference Item (Research - E1)
ISBN: 978-1-4799-0620-8
Date Deposited: 06 Dec 2016 23:31
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation @ 33%
09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090604 Microelectronics and Integrated Circuits @ 33%
10 TECHNOLOGY > 1007 Nanotechnology > 100705 Nanoelectronics @ 34%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 33%
97 EXPANDING KNOWLEDGE > 970110 Expanding Knowledge in Technology @ 33%
97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 34%
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