Depth-Size Tradeoffs for Neural Computation
IEEE Transactions on Computers - Special issue on artificial neural networks
Explicit Constructions of Depth-2 Majority Circuits for Comparison and Addition
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Artificial intelligence: a modern approach
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2-1 Addition and Related Arithmetic Operations with Threshold Logic
IEEE Transactions on Computers
Size--Depth Tradeoffs for Threshold Circuits
SIAM Journal on Computing
The NEURON simulation environment
Neural Computation
Interconnect tuning strategies for high-performance ICs
Proceedings of the conference on Design, automation and test in Europe
The Book of Genesis: Exploring Realistic Neural Models with the General Neural Simulation System
The Book of Genesis: Exploring Realistic Neural Models with the General Neural Simulation System
Synthesis and Optimization of Threshold Logic Networks with Application to Nanotechnologies
Proceedings of the conference on Design, automation and test in Europe - Volume 2
A Threshold Logic Synthesis Tool for RTD Circuits
DSD '04 Proceedings of the Digital System Design, EUROMICRO Systems
Thermal-Aware 3D IC Placement Via Transformation
ASP-DAC '07 Proceedings of the 2007 Asia and South Pacific Design Automation Conference
Depth efficient neural networks for division and related problems
IEEE Transactions on Information Theory
Computational Intelligence and Neuroscience
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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.