@article {46547,
	title = {Lessons from the neurons themselves.},
	journal = {Design Automation Conference (ASP-DAC), 2014 19th Asia and South Pacific},
	year = {2014},
	month = {2014 Jan 20-23},
	pages = {197-200},
	abstract = {<p>Natural neural circuits, optimized by millions of years of evolution, are fast, low power, robust, and adapt in response to experience, all characteristics we would love to have in systems we ourselves design. Recently there have been enormous advances in understanding how neurons implement computations within the brain of living creatures. Can we use this new-found knowledge to create better artificial system? What lessons can we learn from the neurons themselves, that can help us create better neuromorphic circuits?</p>
},
	doi = {10.1109/ASPDAC.2014.6742889},
	author = {Scheffer, LK}
}
@conference {6520,
	title = {Design tools for artificial nervous systems.},
	booktitle = {Design Automation Conference (DAC), 2012 49th ACM/EDAC/IEEE},
	year = {2012},
	month = {2012},
	publisher = {IEEE},
	organization = {IEEE},
	address = {San Francisco, CA},
	abstract = {<p>Electronic and biological systems both perform complex information processing, but they use very different techniques. Though electronics has the advantage in raw speed, biological systems have the edge in many other areas. They can be produced, and indeed self-reproduce, without expensive and finicky factories. They are tolerant of manufacturing defects, and learn and adapt for better performance. In many cases they can self-repair damage. These advantages suggest that biological systems might be useful in a wide variety of tasks involving information processing. So far, all attempts to use the nervous system of a living organism for information processing have involved selective breeding of existing organisms. This approach, largely independent of the details of internal operation, is used since we do not yet understand how neural systems work, nor exactly how they are constructed. However, as our knowledge increases, the day will come when we can envision useful nervous systems and design them based upon what we want them to do, as opposed to variations on what has been already built. We will then need tools, corresponding to our Electronic Design Automation tools, to help with the design. This paper is concerned with what such tools might look like.</p>
},
	isbn = {978-1-4503-1199-1},
	author = {Scheffer, LK}
}
