Answer on Question 44405 - Math - Linear Algebra
B 1 = { [ 1 1 0 1 ] ; [ 1 0 0 1 ] ; [ 1 0 0 − 1 ] } B _ {1} = \left\{\left[ \begin{array}{l l} 1 & 1 \\ 0 & 1 \end{array} \right]; \left[ \begin{array}{l l} 1 & 0 \\ 0 & 1 \end{array} \right]; \left[ \begin{array}{l l} 1 & 0 \\ 0 & - 1 \end{array} \right] \right\} B 1 = { [ 1 0 1 1 ] ; [ 1 0 0 1 ] ; [ 1 0 0 − 1 ] }
and
B 2 = { [ 1 0 0 0 ] ; [ 0 1 0 1 ] ; [ 0 1 0 − 1 ] } B _ {2} = \left\{\left[ \begin{array}{l l} 1 & 0 \\ 0 & 0 \end{array} \right]; \left[ \begin{array}{l l} 0 & 1 \\ 0 & 1 \end{array} \right]; \left[ \begin{array}{l l} 0 & 1 \\ 0 & - 1 \end{array} \right] \right\} B 2 = { [ 1 0 0 0 ] ; [ 0 0 1 1 ] ; [ 0 0 1 − 1 ] }
be 2 bases for span B 1 ⊂ M 2 x 2 ( R ) \operatorname{span} B_1 \subset M_{2x2}(\mathbb{R}) span B 1 ⊂ M 2 x 2 ( R ) with the usual left to right ordering. Let B 3 B_3 B 3 be a basis for P 1 P_1 P 1 and be a transition matrix from B 2 B_2 B 2 to B 3 B_3 B 3 given by
[ 1 1 1 0 1 1 0 0 1 ] = P B 2 → B 3 \left[ \begin{array}{c c c} 1 & 1 & 1 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{array} \right] = P B _ {2} \to B _ {3} ⎣ ⎡ 1 0 0 1 1 0 1 1 1 ⎦ ⎤ = P B 2 → B 3
(a) Find transition matrix P B 1 → B 3 PB_{1}\rightarrow B_{3} P B 1 → B 3 (b) Use P B 2 → B 3 PB_{2}\to B_{3} P B 2 → B 3 to find B 3 B_{3} B 3
Firstly, we notice that bases B 1 B_{1} B 1 and B 2 B_{2} B 2 are bases for linear subspace
B = { [ x y 0 z ] , x , y , z ∈ R } B = \left\{\left[ \begin{array}{c c} x & y \\ 0 & z \end{array} \right], x, y, z \in \mathbb {R} \right\} B = { [ x 0 y z ] , x , y , z ∈ R }
which is isomorphic to R 3 \mathbb{R}^3 R 3 . Let's find respective bases of B B B in R 3 \mathbb{R}^3 R 3 for B 1 B_1 B 1 and B 2 B_2 B 2 . According to B 1 B_1 B 1
B = [ α + β + γ α 0 α + β − γ ] , α , β , γ ∈ R B = \left[ \begin{array}{c c} \alpha + \beta + \gamma & \alpha \\ 0 & \alpha + \beta - \gamma \end{array} \right], \alpha , \beta , \gamma \in \mathbb {R} B = [ α + β + γ 0 α α + β − γ ] , α , β , γ ∈ R
that's why it has a base
P B 1 = { [ 1 1 1 ] , [ 1 0 1 ] , [ 1 0 − 1 ] } P B _ {1} = \left\{\left[ \begin{array}{l} 1 \\ 1 \\ 1 \end{array} \right], \left[ \begin{array}{l} 1 \\ 0 \\ 1 \end{array} \right], \left[ \begin{array}{l} 1 \\ 0 \\ - 1 \end{array} \right] \right\} P B 1 = ⎩ ⎨ ⎧ ⎣ ⎡ 1 1 1 ⎦ ⎤ , ⎣ ⎡ 1 0 1 ⎦ ⎤ , ⎣ ⎡ 1 0 − 1 ⎦ ⎤ ⎭ ⎬ ⎫
Analogically,
P B 2 = { [ 1 0 0 ] , [ 0 1 1 ] , [ 0 1 − 1 ] } P B _ {2} = \left\{\left[ \begin{array}{l} 1 \\ 0 \\ 0 \end{array} \right], \left[ \begin{array}{l} 0 \\ 1 \\ 1 \end{array} \right], \left[ \begin{array}{l} 0 \\ 1 \\ - 1 \end{array} \right] \right\} P B 2 = ⎩ ⎨ ⎧ ⎣ ⎡ 1 0 0 ⎦ ⎤ , ⎣ ⎡ 0 1 1 ⎦ ⎤ , ⎣ ⎡ 0 1 − 1 ⎦ ⎤ ⎭ ⎬ ⎫
It's known that
B 3 → P B 2 = ( P B 2 → B 3 ) − 1 = [ 1 1 1 0 1 1 0 0 1 ] − 1 = [ 1 − 1 0 0 1 − 1 0 0 1 ] [ 1 0 0 0 1 − 1 0 0 1 ] B _ {3} \to P B _ {2} = (P B _ {2} \to B _ {3}) ^ {- 1} = \left[ \begin{array}{l l l} 1 & 1 & 1 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{array} \right] ^ {- 1} = \left[ \begin{array}{l l l} 1 & - 1 & 0 \\ 0 & 1 & - 1 \\ 0 & 0 & 1 \end{array} \right] \left[ \begin{array}{l l l} 1 & 0 & 0 \\ 0 & 1 & - 1 \\ 0 & 0 & 1 \end{array} \right] B 3 → P B 2 = ( P B 2 → B 3 ) − 1 = ⎣ ⎡ 1 0 0 1 1 0 1 1 1 ⎦ ⎤ − 1 = ⎣ ⎡ 1 0 0 − 1 1 0 0 − 1 1 ⎦ ⎤ ⎣ ⎡ 1 0 0 0 1 0 0 − 1 1 ⎦ ⎤
Hence, we can find B 3 B_{3} B 3 as a matrix 3 x 3 3x3 3 x 3
B 3 = B 3 → P B 2 ⋅ P B 2 ⋅ P B 2 → B 3 = [ 1 − 1 0 0 1 − 1 0 0 1 ] [ 1 0 0 0 1 1 0 1 − 1 ] [ 1 1 1 0 1 1 0 0 1 ] = B_{3} = B_{3} \rightarrow P B_{2} \cdot P B_{2} \cdot P B_{2} \rightarrow B_{3} = \begin{bmatrix} 1 & -1 & 0 \\ 0 & 1 & -1 \\ 0 & 0 & 1 \end{bmatrix} \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 1 \\ 0 & 1 & -1 \end{bmatrix} \begin{bmatrix} 1 & 1 & 1 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{bmatrix} = B 3 = B 3 → P B 2 ⋅ P B 2 ⋅ P B 2 → B 3 = ⎣ ⎡ 1 0 0 − 1 1 0 0 − 1 1 ⎦ ⎤ ⎣ ⎡ 1 0 0 0 1 1 0 1 − 1 ⎦ ⎤ ⎣ ⎡ 1 0 0 1 1 0 1 1 1 ⎦ ⎤ = = [ 1 0 − 1 0 0 2 0 1 0 ] = \begin{bmatrix} 1 & 0 & -1 \\ 0 & 0 & 2 \\ 0 & 1 & 0 \end{bmatrix} = ⎣ ⎡ 1 0 0 0 0 1 − 1 2 0 ⎦ ⎤
and B 3 B_{3} B 3 as a span of 2 x 2 2x2 2 x 2 matrices
B 3 = { [ 1 0 0 0 ] ; [ 0 0 0 1 ] ; [ − 1 2 0 0 ] } B_{3} = \left\{ \begin{bmatrix} 1 & 0 \\ 0 & 0 \end{bmatrix}; \begin{bmatrix} 0 & 0 \\ 0 & 1 \end{bmatrix}; \begin{bmatrix} -1 & 2 \\ 0 & 0 \end{bmatrix} \right\} B 3 = { [ 1 0 0 0 ] ; [ 0 0 0 1 ] ; [ − 1 0 2 0 ] }
Due to standard theory of transition matrix
[ 1 0 0 ] = s 11 [ 1 1 1 ] + s 21 [ 1 0 1 ] + s 31 [ 1 0 − 1 ] \begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix} = s_{11} \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix} + s_{21} \begin{bmatrix} 1 \\ 0 \\ 1 \end{bmatrix} + s_{31} \begin{bmatrix} 1 \\ 0 \\ -1 \end{bmatrix} ⎣ ⎡ 1 0 0 ⎦ ⎤ = s 11 ⎣ ⎡ 1 1 1 ⎦ ⎤ + s 21 ⎣ ⎡ 1 0 1 ⎦ ⎤ + s 31 ⎣ ⎡ 1 0 − 1 ⎦ ⎤ [ 0 0 1 ] = s 12 [ 1 1 1 ] + s 22 [ 1 0 1 ] + s 32 [ 1 0 − 1 ] \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix} = s_{12} \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix} + s_{22} \begin{bmatrix} 1 \\ 0 \\ 1 \end{bmatrix} + s_{32} \begin{bmatrix} 1 \\ 0 \\ -1 \end{bmatrix} ⎣ ⎡ 0 0 1 ⎦ ⎤ = s 12 ⎣ ⎡ 1 1 1 ⎦ ⎤ + s 22 ⎣ ⎡ 1 0 1 ⎦ ⎤ + s 32 ⎣ ⎡ 1 0 − 1 ⎦ ⎤ [ − 1 2 0 ] = s 13 [ 1 1 1 ] + s 23 [ 1 0 1 ] + s 33 [ 1 0 − 1 ] \begin{bmatrix} -1 \\ 2 \\ 0 \end{bmatrix} = s_{13} \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix} + s_{23} \begin{bmatrix} 1 \\ 0 \\ 1 \end{bmatrix} + s_{33} \begin{bmatrix} 1 \\ 0 \\ -1 \end{bmatrix} ⎣ ⎡ − 1 2 0 ⎦ ⎤ = s 13 ⎣ ⎡ 1 1 1 ⎦ ⎤ + s 23 ⎣ ⎡ 1 0 1 ⎦ ⎤ + s 33 ⎣ ⎡ 1 0 − 1 ⎦ ⎤
It's easy to show that
s 11 = 0 ; s 21 = 1 2 ; s 31 = 1 2 s_{11} = 0; \quad s_{21} = \frac{1}{2}; \quad s_{31} = \frac{1}{2} s 11 = 0 ; s 21 = 2 1 ; s 31 = 2 1 s 12 = 0 ; s 22 = 1 2 ; s 32 = − 1 2 s_{12} = 0; \quad s_{22} = \frac{1}{2}; \quad s_{32} = \frac{-1}{2} s 12 = 0 ; s 22 = 2 1 ; s 32 = 2 − 1 s 13 = 2 ; s 23 = − 5 2 ; s 33 = − 1 2 s_{13} = 2; \quad s_{23} = \frac{-5}{2}; \quad s_{33} = \frac{-1}{2} s 13 = 2 ; s 23 = 2 − 5 ; s 33 = 2 − 1
So, S = P B 1 → B 3 = S = P B_{1} \rightarrow B_{3} = S = P B 1 → B 3 =
[ 0 0 2 1 2 1 2 − 5 2 1 2 − 1 2 − 1 2 ] \begin{bmatrix} 0 & 0 & 2 \\ \frac{1}{2} & \frac{1}{2} & \frac{-5}{2} \\ \frac{1}{2} & \frac{-1}{2} & \frac{-1}{2} \end{bmatrix} ⎣ ⎡ 0 2 1 2 1 0 2 1 2 − 1 2 2 − 5 2 − 1 ⎦ ⎤
www.AssignmentExpert.com
Comments