acm-header
Sign In

Communications of the ACM

Communications of the ACM

A note on computing approximations to the exponential function


Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values of the argument is the reciprocal of the approximation for corresponding positive values. These methods lead to approximations which are much superior to the commonly used convergents of the Gaussian continued fraction for the exponential. Coefficients and errors are given for the intervals [-1/2 ln 2, 1/2 ln 2] and [-ln 2, ln 2]. Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values of the argument is the reciprocal of the approximation for corresponding positive values. These methods lead to approximations which are much superior to the commonly used convergents of the Gaussian continued fraction for the exponential. Coefficients and errors are given for the intervals [-1/2 ln 2, 1/2 ln 2] and [-ln 2, ln 2].

The full text of this article is premium content


 

No entries found

Log in to Read the Full Article

Sign In

Sign in using your ACM Web Account username and password to access premium content if you are an ACM member, Communications subscriber or Digital Library subscriber.

Need Access?

Please select one of the options below for access to premium content and features.

Create a Web Account

If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.

Join the ACM

Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.
  

Subscribe to Communications of the ACM Magazine

Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.

Purchase the Article

Non-members can purchase this article or a copy of the magazine in which it appears.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account