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In mathematics and computer science, truncation is limiting the number of digits right of the decimal point.

Truncation and floor function

Truncation of positive real numbers can be done using the floor function. Given a number ${\displaystyle x\in \mathbb {R} _{+}}$ to be truncated and ${\displaystyle n\in \mathbb {N} _{0}}$, the number of elements to be kept behind the decimal point, the truncated value of x is

${\displaystyle \operatorname {trunc} (x,n)={\frac {\lfloor 10^{n}\cdot x\rfloor }{10^{n}}}.}$

However, for negative numbers truncation does not round in the same direction as the floor function: truncation always rounds toward zero, the ${\displaystyle \operatorname {floor} }$ function rounds towards negative infinity. For a given number ${\displaystyle x\in \mathbb {R} _{-}}$, the function ${\displaystyle \operatorname {ceil} }$ is used instead

${\displaystyle \operatorname {trunc} (x,n)={\frac {\lceil 10^{n}\cdot x\rceil }{10^{n}}}}$.

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 non-integer real numbers.

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.

See also

• Arithmetic precision
• Quantization (signal processing)
• Precision (computer science)
• Truncation (statistics)

References

1. Spivak, Michael (2008). Calculus (4th ed.). Publish or Perish. p. 434. ISBN 978-0-914098-91-1.

External links

• Wall paper applet that visualizes errors due to finite precision

• Numerical analysis