Abstract
In this paper we study several notions of approximability of functions in the framework of the BSS model. Denoting with ϕ δM the function computed by a BSS machine M when its comparisons are against −δ rather than 0, we study classes of functions f for which ϕ δM → f in some sense (pointwise, uniformly, etc.). The main equivalence results show that this notion coincides with Type 2 computability when the convergence speed is recursively bounded. Finally, we study the possibility of extending these results to computations over Archimedean fields.
The last two authors have been partially supported by the ESPRIT Working Group EP 27150, Neural and Computational Learning II (NeuroCOLT II).
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Meyssonnier, C., Boldi, P., Vigna, S. (2001). δ-Approximable Functions. In: Blanck, J., Brattka, V., Hertling, P. (eds) Computability and Complexity in Analysis. CCA 2000. Lecture Notes in Computer Science, vol 2064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45335-0_12
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DOI: https://doi.org/10.1007/3-540-45335-0_12
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