To find the QR factorization of matrix A using the given orthogonal basis, we can use the formula:
A = QR
where Q is an orthogonal matrix and R is an upper triangular matrix.
The orthogonal basis for A is given as:
Q = ⎡
⎢
⎢
⎢
⎣
−10 2 −6 16 2
3 3 −3 0 3
6 0 6 6 0
0 5 0 0 −5
⎤
⎥
⎥
⎥
⎦
To find matrix R, we can use the formula:
R = Q^T * A
where Q^T is the transpose of matrix Q.
Calculating the transpose of Q:
Q^T = ⎡
⎢
⎢
⎢
⎣
−10 3 6 0
2 3 0 5
−6 −3 6 0
16 0 6 0
2 3 0 −5
⎤
⎥
⎥
⎥
⎦
Calculating R:
R = Q^T * A = ⎡
⎢
⎢
⎢
⎣
−10 3 6 0
2 3 0 5
−6 −3 6 0
16 0 6 0
2 3 0 −5
⎤
⎥
⎥
⎥
⎦ * ⎡
⎢
⎢
⎢
⎣
−10 2 −6 16 2
−4 8 −12 16 8
−1 5 −3 22 5
−1 10 −3 22 0
⎤
⎥
⎥
⎥
⎦
Performing the matrix multiplication:
R = ⎡
⎢
⎢
⎢
⎣
446 -139 189 100
0 14 0 -42
0 0 0 0
0 0 0 0
⎤
⎥
⎥
⎥
⎦
Therefore, the QR factorization of matrix A is:
A = QR, where
Q = ⎡
⎢
⎢
⎢
⎣
−10 2 −6 16 2
3 3 −3 0 3
6 0 6 6 0
0 5 0 0 −5
⎤
⎥
⎥
⎥
⎦
R = ⎡
⎢
⎢
⎢
⎣
446 -139 189 100
0 14 0 -42
0 0 0 0
0 0 0