On the Computational Power of Winner-Take-All

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On the Computational Power of Winner-Take-All
This article initiates a rigorous theoretical analysis of the computational power of circuits that employ modules for computing winner-take-all. Computational models that involve competitive stages have so far been neglected in computational complexity theory, although they are widely used in computational brain models, artificial neural networks, and analog VLSI. Our theoretical analysis shows that winner-take-all is a surprisingly powerful computational module in comparison with threshold gates (= McCullochPitts neurons) and sigmoidal gates. We prove an optimal quadratic lower bound for computing winner-take-all in any feedforward circuit consisting of threshold gates. In addition we show that arbitrary continuous functions can be approximated by circuits employing a single soft winner-take-all gate as their only nonlinear operation. Our theoretical analysis also provides answers to two basic questions that have been raised by neurophysiologists in view of the well-known asymmetry b...
Wolfgang Maass
Added 18 Dec 2010
Updated 18 Dec 2010
Type Journal
Year 2000
Where ECCC
Authors Wolfgang Maass
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