A fast, compact approximation of the exponential function.

N N Schraudolph

doi:10.1162/089976699300016467

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A fast, compact approximation of the exponential function.

N N Schraudolph

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Abstract

Neural network simulations often spend a large proportion of their time computing exponential functions. Since the exponentiation routines of typical math libraries are rather slow, their replacement with a fast approximation can greatly reduce the overall computation time. This article describes how exponentiation can be approximated by manipulating the components of a standard (IEEE-754) floating-point representation. This models the exponential function as well as a lookup table with linear interpolation, but is significantly faster and more compact.

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Algorithms Logistic Models Neural Networks, Computer Nonlinear Dynamics Reproducibility of Results Journal Article Research Support, Non-U.S. Gov't

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N N Schraudolph. 1999-05-15. A fast, compact approximation of the exponential function.. https://doi.org/10.1162/089976699300016467

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