Hybrid computation with an attractor neural network | IEEE Conference Publication | IEEE Xplore

Hybrid computation with an attractor neural network


Abstract:

This paper discusses the properties of a controllable, flexible, hybrid parallel computing architecture that potentially merges pattern recognition and arithmetic. Humans...Show More

Abstract:

This paper discusses the properties of a controllable, flexible, hybrid parallel computing architecture that potentially merges pattern recognition and arithmetic. Humans perform integer arithmetic in a fundamentally different way than logic-based computers. Even though the human approach to arithmetic is slow and inaccurate for purely arithmetic computation, it can have substantial advantages when useful approximations ("intuition") are more valuable than high precision. Such a computational strategy may be particularly useful when computers based on nanocomponents become feasible because it offers a way to make use of the potential power of these massively parallel systems.
Date of Conference: 19-20 August 2002
Date Added to IEEE Xplore: 10 December 2002
Print ISBN:0-7695-1724-2
Conference Location: Calgary, AB, Canada

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