1 May 2008—Anyone familiar with electronics knows the trinity of fundamental components: the resistor, the capacitor, and the inductor. In 1971, a University of California, Berkeley, engineer predicted that there should be a fourth element: a memory resistor, or memristor. But no one knew how to build one. Now, 37 years later, electronics have finally gotten small enough to reveal the secrets of that fourth element. The memristor, Hewlett-Packard researchers revealed today in the journal Nature, had been hiding in plain sight all along—within the electrical characteristics of certain nanoscale devices. They think the new element could pave the way for applications both near- and far-term, from nonvolatile RAM to realistic neural networks.
By Sally Adee, IEEE’s Spectrum Issue May 2008
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IQR provides an efficient graphical environment to design large-scale multi-level neuronal systems that can control real-world devices – robots in the broader sense – in real-time.
IQR has been released as open-source under GNU General Public License (GPL)
IRQ is written by Ulysses Bernardet, Institute of Neuroinformatics
University, ETH Zurich.
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Why Can’t A Computer Be More Like A Brain?
“Computers, at long last, can play winning chess. But the program that can beat the world champion can’t talk about chess, let alone learn backgammon. Today’s programs-at best-solve specific problems. Where humans have broad and flexible capabilities, computers do not. ”
Source: IEEE Spectrum Magazine
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Biological neural networks are large systems of complex elements interacting through a complex array of connections.
How do we describe and interpret the activity of a large
population of neurons and how do we model neural circuits when:
o individual neurons are such complex elements and
o our knowledge of the synaptic connections is so incomplete?
A review paper by L.F. Abbott
Center for Complex Systems
Brandeis University
Waltham, MA 02254
Published in Quart. Rev. Biophys. 27:291-331 (1994)
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