Towards Development on a Silicon-based Cellular Computing Machine
Natural Computing: an international journal
Design of an application-specific PLD architecture
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Real-time reconfigurable linear threshold elements and some applications to neural hardware
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
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Many believe that the most important result to come out of the last ten years of neural network research is the significant change in perspective in the neuroscience community towards a theory of computational neurobiology and functional neuro-models. Arriving on a fast moving train from the other direction is semiconductor technology, one of the greatest technology success stories of all time - transistors are now approaching deep submicron (less than 100 nanometers) in size, and we will soon be building silicon chips with over 1 billion transistors. The marriage of these two technologies is creating what Andy Grove (ex-CEO of Intel) refers to as a strategic inflection point. Although previous attempts at merging these technologies were premature, silicon and computational neurobiology are now merging to create an extremely powerful, and radically new form of computation.