In mathematics, a function on the real numbers is called a step function if it can be written as a finite linear combination of indicator functions of intervals. Informally speaking, a step function is a piecewise constant function having only finitely many pieces.

Definition and first consequences
A function
f
:
R
→
R
{\displaystyle f\colon \mathbb {R} \rightarrow \mathbb {R} }
is called a step function if it can be written as
-
f
(
x
)
=
∑
i
=
0
n
α
i
χ
A
i
(
x
)
{\displaystyle f(x)=\sum \limits _{i=0}^{n}\alpha _{i}\chi _{A_{i}}(x)}
, for all real numbers x {\displaystyle x}
where
n
≥
0
{\displaystyle n\geq 0}
,
α
i
{\displaystyle \alpha _{i}}
are real numbers,
A
i
{\displaystyle A_{i}}
are intervals, and
χ
A
i
{\displaystyle \chi _{A_{i}}}
is the indicator function of
A
i
{\displaystyle A_{i}}
:
-
χ
A
i
(
x
)
=
{
1
if
x
∈
A
i
0
if
x
∉
A
i
{\displaystyle \chi _{A_{i}}(x)={\begin{cases}1&{\text{if }}x\in A_{i}\\0&{\text{if }}x\notin A_{i}\\\end{cases}}}
In this definition, the intervals
A
i
{\displaystyle A_{i}}
can be assumed to have the following two properties:
- The intervals are pairwise disjoint:
A
i
∩
A
j
=
∅
{\displaystyle A_{i}\cap A_{j}=\emptyset }
for i ≠ j {\displaystyle i\neq j}
- The union of the intervals is the entire real line:
⋃
i
=
0
n
A
i
=
R
.
{\displaystyle \bigcup _{i=0}^{n}A_{i}=\mathbb {R} .}
Indeed, if that is not the case to start with, a different set of intervals can be picked for which these assumptions hold. For example, the step function
-
f
=
4
χ
[
−
5
,
1
)
+
3
χ
(
0
,
6
)
{\displaystyle f=4\chi _{[-5,1)}+3\chi _{(0,6)}}
can be written as
-
f
=
0
χ
(
−
∞
,
−
5
)
+
4
χ
[
−
5
,
0
]
+
7
χ
(
0
,
1
)
+
3
χ
[
1
,
6
)
+
0
χ
[
6
,
∞
)
.
{\displaystyle f=0\chi _{(-\infty ,-5)}+4\chi _{[-5,0]}+7\chi _{(0,1)}+3\chi _{[1,6)}+0\chi _{[6,\infty )}.}
Variations in the definition
Sometimes, the intervals are required to be right-open[1] or allowed to be singleton.[2] The condition that the collection of intervals must be finite is often dropped, especially in school mathematics,[3][4][5] though it must still be locally finite, resulting in the definition of piecewise constant functions.
Examples

- A constant function is a trivial example of a step function. Then there is only one interval,
A
0
=
R
.
{\displaystyle A_{0}=\mathbb {R} .}
- The sign function sgn(x), which is −1 for negative numbers and +1 for positive numbers, and is the simplest non-constant step function.
- The Heaviside function H(x), which is 0 for negative numbers and 1 for positive numbers, is equivalent to the sign function, up to a shift and scale of range (
H
=
(
sgn
+
1
)
/
2
{\displaystyle H=(\operatorname {sgn} +1)/2}
). It is the mathematical concept behind some test signals, such as those used to determine the step response of a dynamical system.

- The rectangular function, the normalized boxcar function, is used to model a unit pulse.
Non-examples
- The integer part function is not a step function according to the definition of this article, since it has an infinite number of intervals. However, some authors also define step functions with an infinite number of intervals.[6]
Properties
- The sum and product of two step functions is again a step function. The product of a step function with a number is also a step function. As such, the step functions form an algebra over the real numbers.
- A step function takes only a finite number of values. If the intervals
A
i
,
{\displaystyle A_{i},}
for i = 0 , 1 , … , n {\displaystyle i=0,1,\dots ,n}
in the above definition of the step function are disjoint and their union is the real line, then f ( x ) = α i {\displaystyle f(x)=\alpha _{i}}
for all x ∈ A i . {\displaystyle x\in A_{i}.}
- The definite integral of a step function is a piecewise linear function.
- The Lebesgue integral of a step function
f
=
∑
i
=
0
n
α
i
χ
A
i
{\displaystyle \textstyle f=\sum _{i=0}^{n}\alpha _{i}\chi _{A_{i}}}
is ∫ f d x = ∑ i = 0 n α i ℓ ( A i ) , {\displaystyle \textstyle \int f\,dx=\sum _{i=0}^{n}\alpha _{i}\ell (A_{i}),}
where ℓ ( A ) {\displaystyle \ell (A)}
is the length of the interval A {\displaystyle A}
, and it is assumed here that all intervals A i {\displaystyle A_{i}}
have finite length. In fact, this equality (viewed as a definition) can be the first step in constructing the Lebesgue integral.[7]
- A discrete random variable is sometimes defined as a random variable whose cumulative distribution function is piecewise constant.[8] In this case, it is locally a step function (globally, it may have an infinite number of steps). Usually however, any random variable with only countably many possible values is called a discrete random variable, in this case their cumulative distribution function is not necessarily locally a step function, as infinitely many intervals can accumulate in a finite region.
See also
References
- "Step Function".
- "Step Functions - Mathonline".
- "Mathwords: Step Function".
- "Archived copy". Archived from the original on 2015-09-12. Retrieved 2024-12-16.
{{cite web}}: CS1 maint: archived copy as title (link) - "Step Function".
- Bachman, Narici, Beckenstein (5 April 2002). "Example 7.2.2". Fourier and Wavelet Analysis. Springer, New York, 2000. ISBN 0-387-98899-8.
{{cite book}}: CS1 maint: multiple names: authors list (link) - Weir, Alan J (10 May 1973). "3". Lebesgue integration and measure. Cambridge University Press, 1973. ISBN 0-521-09751-7.
- Bertsekas, Dimitri P. (2002). Introduction to Probability. Tsitsiklis, John N., Τσιτσικλής, Γιάννης Ν. Belmont, Mass.: Athena Scientific. ISBN 188652940X. OCLC 51441829.