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- W2017291505 abstract "Interest in computing continuous functions arises in our case from the need for a model of computing applicable to economic models, which typically are formulated in terms of real variables and continuous functions. One standard way to study the task of computing a continuous function is to approximate the function on a finite grid and to analyze the resulting tinite computing problem. This introduces a gap between the computation analyzed and the desired analysis. Generally results may depend on the particular approximation chosen as well as on the function we are really interested in. A complete analysis should therefore in some way separate and identify those results due to approximation and those intrinsic to the underlying continuous function. Our approach is to formulate a model of continuous computing which permits direct analysis of computing continuous functions. This ap preach raises the question, How do the results obtained from a continuous model relate to results obtained from finite models, the models of “real” computing? This paper addresses that question in the context of a particular model of continuous computing and its underlying finite state analog, McCulloch-Pius networks. We note three properties that a model of continuous computing should have in order to be applicable to economic models:" @default.
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- W2017291505 date "1985-10-01" @default.
- W2017291505 modified "2023-10-16" @default.
- W2017291505 title "Approximation in a continuous model of computing" @default.
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- W2017291505 doi "https://doi.org/10.1016/0885-064x(85)90027-5" @default.
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