Analog VLSI implementation of a spike driven stochastic dynamical synapse View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1998

AUTHORS

Mario Annunziato , Davide Badoni , Stefano Fusi , Andrea Salamon

ABSTRACT

We have undertaken to implement in analog electronics a neural network device which autonomously learns from its experience in real time. Implementing a large neural network that has this capability, implies analog VLSI technology and on-chip learning. This means designing a plastic synaptic connection that 1. is simple (low number of transistors and reduced silicon area), 2. has low power consumption and 3. preserves memory on long time scales and, at the same time, can be modified in short time intervals during stimulation. More... »

PAGES

475-480

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4471-1599-1_71

DOI

http://dx.doi.org/10.1007/978-1-4471-1599-1_71

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019653847


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