Thm_
Let V,W,Z be vector spaces over F, and let T:V→W & U:W→Z be linear. Then UT=U∘T:V→Z is linear.
Thm_
Let V be a vector space. Let T,U1,U2∈L(V)=L(V,V). Then
(a) T(U1+U2)=TU1+TU2,(U1+U2)T=U1T+U2T
(b) T(U1U2)=(TU1)U2
(c) IT=TI=T (I:V→ is the identity map)
(c) a(U1U2)=(aU1)U2=U1(aU2)∀a∈F
(Caution, U1U2≠U2U1 in general.)
CompostionvsMatrixProduct_
Let T:V→W,U:W→Z be linear. where α={v1,⋯,vp},β={w1,⋯,wn},γ={z1,⋯,zm} are ordered basis for V,W,Z, respectively.
Let A=(aik)m×n=[U]γβ,B=(bkj)n×p=[T]βα,C=(cij)m×p=[UT]γα.
Then
T(vj)=n∑k=1bkjwk(1≤j≤p)
U(wk)=m∑i=1aikzi(1≤k≤n)
(UT)(vj)=m∑i=1cijzi(1≤j≤p)
On the other hand,
(UT)(vj)=U(T(vj))=U(n∑k=1bkjwk)=n∑k=1bkjm∑i=1aikzi=m∑i=1(n∑k=1aikbkj)zi
Thus,
cij=n∑k=1aikbkj(1≤i≤m,1≤j≤p).
Def_
Let A∈Mm×n(F),B∈Mn×p(F).
The product AB of A & B is defined to be the matrix AB∈Mm×p(F) given by
(AB)ij=n∑k=1AikBkj(1≤i≤m,1≤j≤p).
With this definition, we have proved the following above.
Thm_
Let V,W,Z be finite dimensional vector spaces with ordered bases α,β,γ, respectively.
Let T:V→W,U:W→Z be linear.
Then [UT]γα=[U]γβ[T]βα.
Prop_
Let A∈Mm×n=Mm×n(F),B∈Mn×p.
Then (AB)t=BtAt
Proof_
(AB)tij=(AB)ij=n∑k=1AjkBki=n∑k=1(Bt)ik(At)ki=(BtAt)ijfor1≤i≤p,1≤j≤m
'수학 > 선형대수학' 카테고리의 다른 글
[선형대수학] 행렬의 거듭제곱 (Power of Matrix) (0) | 2020.08.26 |
---|---|
[선형대수학] 행렬 연산의 성질 (Properties of Matrix Operation) (0) | 2020.08.26 |
[선형대수학] 선형 사상을 모은 집합과 행렬을 모은 집합 간에는 선형 사상이 존재한다. (Existence of Linear Map Between Set of Linear Maps and Set of Matrices) (0) | 2020.08.24 |
[선형대수학] 벡터 공간 간의 사상을 모은 집합은 벡터 공간이 된다. (0) | 2020.08.24 |
[선형대수학] 선형 변환의 행렬 표현 (Matrix Representation of a Linear Transform) (0) | 2020.08.21 |