Let matrix A represent an orthogonal projection onto the subspace V, where V is the plane x + 2y + 3z = 0 in R3. a) Find a basis of im(A). b) Find a basis of ker(A). c) Find the orthogonal projection of the vector ⃗v = [1 2 3] onto V
Let matrix A represent an orthogonal projection onto the subspace V, where V is the plane x + 2y + 3z = 0 in R3. a) Find a basis of im(A). b) Find a basis of ker(A). c) Find the orthogonal projection of the vector ⃗v = [1 2 3] onto V
Let matrix A represent an orthogonal projection onto the subspace V, where V is the plane x + 2y + 3z = 0 in R3. a) Find a basis of im(A). b) Find a basis of ker(A). c) Find the orthogonal projection of the vector ⃗v = [1 2 3] onto V
Let matrix A represent an orthogonal projection onto the subspace V, where V is the plane x + 2y + 3z = 0 in R3.
a) Find a basis of im(A). b) Find a basis of ker(A).
c) Find the orthogonal projection of the vector ⃗v = [1 2 3] onto V
Quantities that have magnitude and direction but not position. Some examples of vectors are velocity, displacement, acceleration, and force. They are sometimes called Euclidean or spatial vectors.
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