在数学 上,二项式系数 是二项式定理 中各项的系数 。一般而言,二项式系数由两个非负整数
n
{\displaystyle n}
和
k
{\displaystyle k}
为参数决定,写作
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
,定义为
(
1
+
x
)
n
{\displaystyle (1+x)^{n}}
的多项式展开式中,
x
k
{\displaystyle x^{k}}
项的系数 ,因此一定是非负整数。如果将二项式系数
(
n
0
)
,
(
n
1
)
,
…
,
(
n
n
)
{\displaystyle {\binom {n}{0}},{\binom {n}{1}},\dots ,{\binom {n}{n}}}
写成一行,再依照
n
=
0
,
1
,
2
,
…
{\displaystyle n=0,1,2,\dots }
顺序由上往下排列,则构成帕斯卡三角形 。
二项式系数可排列成帕斯卡三角形
二项式系数常见于各数学领域中,尤其是组合数学 。事实上,
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
可以被理解为从
n
{\displaystyle n}
个相异元素中取出
k
{\displaystyle k}
个元素的方法数,所以
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
大多读作“
n
{\displaystyle n}
取
k
{\displaystyle k}
”。二项式系数
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
的定义可以推广至
n
{\displaystyle n}
是复数 的情况,而且仍然被称为二项式系数。
除展开二项式或点算组合数量之外,尚有多种方式计算
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
的值。
以下递归 公式可计算二项式系数:
(
n
k
)
=
(
n
−
1
k
−
1
)
+
(
n
−
1
k
)
∀
n
,
k
∈
N
{\displaystyle {\binom {n}{k}}={\binom {n-1}{k-1}}+{\binom {n-1}{k}}\quad \forall n,k\in \mathbb {N} }
其中特别指定:
(
n
0
)
=
1
∀
n
∈
N
∪
{
0
}
,
{\displaystyle {\binom {n}{0}}=1\quad \forall n\in \mathbb {N} \cup \{0\},}
(
0
k
)
=
0
∀
k
∈
N
.
{\displaystyle {\binom {0}{k}}=0\quad \forall k\in \mathbb {N} .}
此公式可由计算
(
1
+
x
)
n
−
1
(
1
+
x
)
{\displaystyle (1+x)^{n-1}(1+x)}
中的
x
k
{\displaystyle x^{k}}
项,或点算集合
{
1
,
2
,
⋯
,
n
}
{\displaystyle \left\{1,2,\cdots ,n\right\}}
的
k
{\displaystyle k}
个元素组合中包含
n
{\displaystyle n}
与不包含
n
{\displaystyle n}
的数量得出。
显然,如果
k
>
n
{\displaystyle k>n}
,则
(
n
k
)
=
0
{\displaystyle {\tbinom {n}{k}}=0}
。而且对所有
n
{\displaystyle n}
,
(
n
n
)
=
1
{\displaystyle {\tbinom {n}{n}}=1}
,故此上述递归公式可于此等情况下中断。递归公式可用作建构帕斯卡三角形 。
∑
r
=
0
n
(
n
r
)
=
2
n
{\displaystyle \sum _{r=0}^{n}{\binom {n}{r}}=2^{n}}
∑
r
=
0
k
(
n
+
r
−
1
r
)
=
(
n
+
k
k
)
{\displaystyle \sum _{r=0}^{k}{\binom {n+r-1}{r}}={\binom {n+k}{k}}}
∑
r
=
0
n
−
k
(
−
1
)
r
(
n
+
1
)
k
+
r
+
1
(
n
−
k
r
)
=
(
n
k
)
−
1
{\displaystyle \sum _{r=0}^{n-k}{\frac {(-1)^{r}(n+1)}{k+r+1}}{\binom {n-k}{r}}={\binom {n}{k}}^{-1}}
∑
r
=
0
n
(
d
n
d
r
)
=
1
d
∑
r
=
1
d
(
1
+
e
2
π
r
i
d
)
d
n
{\displaystyle \sum _{r=0}^{n}{\binom {dn}{dr}}={\frac {1}{d}}\sum _{r=1}^{d}(1+e^{\frac {2\pi ri}{d}})^{dn}}
[ 参 3]
∑
i
=
m
n
(
a
+
i
i
)
=
(
a
+
n
+
1
n
)
−
(
a
+
m
m
−
1
)
{\displaystyle \sum _{i=m}^{n}{\binom {a+i}{i}}={\binom {a+n+1}{n}}-{\binom {a+m}{m-1}}}
(
a
+
m
m
−
1
)
+
(
a
+
m
m
)
+
(
a
+
m
+
1
m
+
1
)
+
.
.
.
+
(
a
+
n
n
)
=
(
a
+
n
+
1
n
)
{\displaystyle {\binom {a+m}{m-1}}+{\binom {a+m}{m}}+{\binom {a+m+1}{m+1}}+...+{\binom {a+n}{n}}={\binom {a+n+1}{n}}}
F
n
=
∑
i
=
0
∞
(
n
−
i
i
)
{\displaystyle F_{n}=\sum _{i=0}^{\infty }{\binom {n-i}{i}}}
[ 参 4]
F
n
−
1
+
F
n
=
∑
i
=
0
∞
(
n
−
1
−
i
i
)
+
∑
i
=
0
∞
(
n
−
i
i
)
=
1
+
∑
i
=
1
∞
(
n
−
i
i
−
1
)
+
∑
i
=
1
∞
(
n
−
i
i
)
=
1
+
∑
i
=
1
∞
(
n
+
1
−
i
i
)
=
∑
i
=
0
∞
(
n
+
1
−
i
i
)
=
F
n
+
1
{\displaystyle F_{n-1}+F_{n}=\sum _{i=0}^{\infty }{\binom {n-1-i}{i}}+\sum _{i=0}^{\infty }{\binom {n-i}{i}}=1+\sum _{i=1}^{\infty }{\binom {n-i}{i-1}}+\sum _{i=1}^{\infty }{\binom {n-i}{i}}=1+\sum _{i=1}^{\infty }{\binom {n+1-i}{i}}=\sum _{i=0}^{\infty }{\binom {n+1-i}{i}}=F_{n+1}}
∑
i
=
m
n
(
i
a
)
=
(
n
+
1
a
+
1
)
−
(
m
a
+
1
)
{\displaystyle \sum _{i=m}^{n}{\binom {i}{a}}={\binom {n+1}{a+1}}-{\binom {m}{a+1}}}
(
m
a
+
1
)
+
(
m
a
)
+
(
m
+
1
a
)
.
.
.
+
(
n
a
)
=
(
n
+
1
a
+
1
)
{\displaystyle {\binom {m}{a+1}}+{\binom {m}{a}}+{\binom {m+1}{a}}...+{\binom {n}{a}}={\binom {n+1}{a+1}}}
∑
r
=
0
n
(
n
r
)
2
=
(
2
n
n
)
{\displaystyle \sum _{r=0}^{n}{\binom {n}{r}}^{2}={\binom {2n}{n}}}
∑
i
=
0
n
(
r
1
+
n
−
1
−
i
r
1
−
1
)
(
r
2
+
i
−
1
r
2
−
1
)
=
(
r
1
+
r
2
+
n
−
1
r
1
+
r
2
−
1
)
{\displaystyle \sum _{i=0}^{n}{\binom {r_{1}+n-1-i}{r_{1}-1}}{\binom {r_{2}+i-1}{r_{2}-1}}={\binom {r_{1}+r_{2}+n-1}{r_{1}+r_{2}-1}}}
[ 参 5]
(
1
−
x
)
−
r
1
(
1
−
x
)
−
r
2
=
(
1
−
x
)
−
r
1
−
r
2
{\displaystyle (1-x)^{-r_{1}}(1-x)^{-r_{2}}=(1-x)^{-r_{1}-r_{2}}}
(
1
−
x
)
−
r
1
(
1
−
x
)
−
r
2
=
(
∑
n
=
0
∞
(
r
1
+
n
−
1
r
1
−
1
)
x
n
)
(
∑
n
=
0
∞
(
r
2
+
n
−
1
r
2
−
1
)
x
n
)
=
∑
n
=
0
∞
(
∑
i
=
0
n
(
r
1
+
n
−
1
−
i
r
1
−
1
)
(
r
2
+
i
−
1
r
2
−
1
)
)
x
n
{\displaystyle (1-x)^{-r_{1}}(1-x)^{-r_{2}}=(\sum _{n=0}^{\infty }{\binom {r_{1}+n-1}{r_{1}-1}}x^{n})(\sum _{n=0}^{\infty }{\binom {r_{2}+n-1}{r_{2}-1}}x^{n})=\sum _{n=0}^{\infty }(\sum _{i=0}^{n}{\binom {r_{1}+n-1-i}{r_{1}-1}}{\binom {r_{2}+i-1}{r_{2}-1}})x^{n}}
(
1
−
x
)
−
r
1
−
r
2
=
∑
n
=
0
∞
(
r
1
+
r
2
+
n
−
1
r
1
+
r
2
−
1
)
x
n
{\displaystyle (1-x)^{-r_{1}-r_{2}}=\sum _{n=0}^{\infty }{\binom {r_{1}+r_{2}+n-1}{r_{1}+r_{2}-1}}x^{n}}
∑
i
=
0
k
(
n
i
)
(
m
k
−
i
)
=
(
n
+
m
k
)
{\displaystyle \sum _{i=0}^{k}{\binom {n}{i}}{\binom {m}{k-i}}={\binom {n+m}{k}}}
(
n
+
k
k
)
2
=
∑
j
=
0
k
(
k
j
)
2
(
n
+
2
k
−
j
2
k
)
{\displaystyle {\binom {n+k}{k}}^{2}=\sum _{j=0}^{k}{\binom {k}{j}}^{2}{\binom {n+2k-j}{2k}}}
见(Graham, Knuth & Patashnik 1994 ),其中就
k
<
0
{\displaystyle k<0}
定义了
(
n
k
)
=
0
{\displaystyle {\tbinom {n}{k}}=0}
,其他一般化形式包括考虑两参数为实数或复数 时以伽玛函数 为
k
<
0
{\displaystyle k<0}
时定义
(
n
k
)
{\displaystyle {\tbinom {n}{k}}}
,但此举会令大部分二项式系数的恒等式失效,故未有被广泛采用。然而,此方法替不等于零的参数下定义则可得出如Hilton, Holton and Pedersen, Mathematical reflections: in a room with many mirrors , Springer, 1997中那种好看的“帕斯卡风车”,但是却会令帕斯卡法则 在原点失效。
此可视作泰勒定理 的离散形式,亦与牛顿多项式 有关,此式的交错项之和可以Nörlund–Rice积分 表示。
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