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Synaptic plasticity and spike-based computation in VLSI networks of integrate-and-fire neurons


Indiveri, G (2007). Synaptic plasticity and spike-based computation in VLSI networks of integrate-and-fire neurons. Neural Information Processing - Letters and Reviews, 11(4-6):135-146.

Abstract

euromorphic circuits are being used to develop a new generation of computing technologies based on the organizing principles of the biological nervous system. Within this context, we present neuromorphic circuits for implementing massively parallel VLSI networks of integrate-and-fire neurons with adaptation and spike-based plasticity mechanisms. We describe both analog continuous time and digital asynchronous event-based circuits for constructing spiking neural network devices, and present a VLSI implementation of a spikebased learning mechanisms for carrying out robust classification of spatio-temporal patterns, and real–time sensory signal processing. We argue that these types of devices have great potential for exploiting future scaled VLSI processes and are ideal for implementing sensorymotor processing units on autonomous and humanoid robots.

Abstract

euromorphic circuits are being used to develop a new generation of computing technologies based on the organizing principles of the biological nervous system. Within this context, we present neuromorphic circuits for implementing massively parallel VLSI networks of integrate-and-fire neurons with adaptation and spike-based plasticity mechanisms. We describe both analog continuous time and digital asynchronous event-based circuits for constructing spiking neural network devices, and present a VLSI implementation of a spikebased learning mechanisms for carrying out robust classification of spatio-temporal patterns, and real–time sensory signal processing. We argue that these types of devices have great potential for exploiting future scaled VLSI processes and are ideal for implementing sensorymotor processing units on autonomous and humanoid robots.

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Additional indexing

Item Type:Journal Article, not refereed, further contribution
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2007
Deposited On:19 Mar 2014 14:23
Last Modified:08 Dec 2017 04:26
Publisher:KAIST Press
Number of Pages:12
ISSN:1738-2564
Free access at:Official URL. An embargo period may apply.
Official URL:http://bsrc.kaist.ac.kr/nip-lr/V11N04-06/V11N04P8-135-146.pdf
Related URLs:http://bsrc.kaist.ac.kr/nip-lr/V11N04-06/V11N04-06.htm

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