Truncation: Difference between revisions
moved sentence with Creighton Sweeney above "For example, consider..." |
Removed unverifiable information. |
||
Line 2: | Line 2: | ||
In [[mathematics]] and [[computer science]], '''truncation''' is the term for limiting the number of [[numerical digit|digit]]s right of the [[decimal point]], by discarding the least significant ones. |
In [[mathematics]] and [[computer science]], '''truncation''' is the term for limiting the number of [[numerical digit|digit]]s right of the [[decimal point]], by discarding the least significant ones. |
||
The term was first used in television by Creighton Sweeney. |
|||
For example, consider the [[real number]]s |
For example, consider the [[real number]]s |
Revision as of 09:22, 6 November 2014
In mathematics and computer science, truncation is the term for limiting the number of digits right of the decimal point, by discarding the least significant ones.
For example, consider the real numbers
- 5.6341432543653654
- 32.438191288
- −6.3444444444444
To truncate these numbers to 4 decimal digits, we only consider the 4 digits to the right of the decimal point.
The result would be:
- 5.6341
- 32.4381
- −6.3444
Truncation is equivalent to rounding towards zero (or rounding down the absolute value of the number while maintaining the sign).
The truncation error can be twice the maximum error in rounding.[citation needed]
Truncation and floor function
Truncation of positive real numbers can be done using the floor function. Given a number to be truncated and , the number of elements to be kept behind the decimal point, the truncated value of x is
However, for negative numbers truncation does not round in the same direction as the floor function: truncation always rounds toward zero, the floor function rounds towards negative infinity.
Causes of truncation
With computers, truncation can occur when a decimal number is typecast as an integer; it is truncated to zero decimal digits because integers cannot store real numbers (that are not themselves integers).
In algebra
An analogue of truncation can be applied to polynomials. In this case, the truncation of a polynomial P to degree n can be defined as the sum of all terms of P of degree n or less. Polynomial truncations arise in the study of Taylor polynomials, for example.[1]
See also
- Arithmetic precision
- Floor function
- Quantization (signal processing)
- Precision (computer science)
- Truncation (statistics)
References
- ^ Spivak, Michael (2008). Calculus (4th ed.). p. 434. ISBN 978-0-914098-91-1.
External links
- Wall paper applet that visualizes errors due to finite precision