All vectors and subspaces are in Rn. Note you only have 5 attempts for this question. Check the true statements below: - A. If a matrix A is such that AT A then the perpendicular complement of the kernel of A is the image of A. B. For each y and each subspace W, the vector y - projw(y) is orthogonal to W. C. The columns of a matrix A are perpendicular to the rows of AT. D. If y is in a subspace W, then the orthogonal projection of y onto W is y itself. E. If z is orthogonal to u₁ and u₂ and if W=span( u₁, u2), then z must be in W+.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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All vectors and subspaces are in Rr. Note you only have 5 attempts for this question.
Check the true statements below:
A. If a matrix A is such that AT
=
A then the perpendicular complement of the kernel of A is the image of A.
B. For each y and each subspace W, the vector y - projw(y) is orthogonal to W.
C. The columns of a matrix A are perpendicular to the rows of AT.
D. If y is in a subspace W, then the orthogonal projection of y onto W is y itself.
E. If z is orthogonal to u₁ and u₂ and if W=span( u₁, u2), then z must be in W¹.
F. The closest vector to y in a subspace W is given by the vector y - projw(y).
| G. If y = %1 + 22, where 21 is in a subspace W and 22 is in W₁, then 21 must be the orthogonal projection of y onto W.
H. If W is a subspace and if v is in both W and W+, then v must be the zero vector.
I. The orthogonal projection x of y onto a subspace W can sometimes depend on the matrix used to compute x.
Transcribed Image Text:All vectors and subspaces are in Rr. Note you only have 5 attempts for this question. Check the true statements below: A. If a matrix A is such that AT = A then the perpendicular complement of the kernel of A is the image of A. B. For each y and each subspace W, the vector y - projw(y) is orthogonal to W. C. The columns of a matrix A are perpendicular to the rows of AT. D. If y is in a subspace W, then the orthogonal projection of y onto W is y itself. E. If z is orthogonal to u₁ and u₂ and if W=span( u₁, u2), then z must be in W¹. F. The closest vector to y in a subspace W is given by the vector y - projw(y). | G. If y = %1 + 22, where 21 is in a subspace W and 22 is in W₁, then 21 must be the orthogonal projection of y onto W. H. If W is a subspace and if v is in both W and W+, then v must be the zero vector. I. The orthogonal projection x of y onto a subspace W can sometimes depend on the matrix used to compute x.
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