Journal
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
Volume 31, Issue 1, Pages 37-53Publisher
WILEY
DOI: 10.1002/cta.223
Keywords
single-electron devices; nanowires; nanoFETs; hybrid circuits; neuromorphic networks; synapses; crossbar arrays; self-evolution; adaptation
Categories
Ask authors/readers for more resources
Extremely dense neuromorphic networks may be based on hybrid 2D arrays of nanoscale components, including molecular latching switches working as adaptive synapses, nanowires as axons and dendrites, and nano-CMOS circuits serving as neural cell bodies. Possible architectures include 'free-growing' networks that may form topologies very close to those of cerebral cortex, and several species of distributed crossbar-type networks, 'CrossNets' (including notably 'InBar' and 'RandBar'), with better density and speed scaling. Numerical modelling show that the specific signal sign asymmetry used in CrossNets allows self-excitation of recurrent networks with long-range cell interaction, without a symmetry-breaking global latchup. Our next goal is to develop methods of globally supervised teaching of extremely large networks with no external access to individual synapses. Such development would open a way towards cerebral-cortex-scale networks (with similar to 10(10) neural cells and similar to 10(14) synapses) capable of advanced information processing and self-evolution at a speed several orders of magnitude higher than their biological prototypes. Copyright (C) 2003 John Wiley Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available