A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is
In this paper we describe our approach towards highly configurable neuromorphic hardware systems that serve as useful and flexible tools in modeling neuroscience. We utilize a mixed-signal VLSI model that implements a massively accelerated network of spiking neurons, and we describe a novel methodological framework that allows to exploit both the speed and the programmability of this device for the systematic and simulator-like exploration of cortical network architectures. We present a varietydoi:10.1109/iscas.2010.5537005 dblp:conf/iscas/BruderleBKKMMS10a fatcat:pu2y2queyzf2ddnrfowbaykyqy