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set of vectors which can be added and scaled (without leaving the space!) |
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Subspace of vector space (H of V) |
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The zero vector of V is in H Combinations of the subspace (u + v) are in H Can multiply by a scalar and be in H |
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1) REF augmented matrix with 0 ([A|0)
2) Write solution as linear combination (ex:
(x1,x2,x3) = (1,2,3)x1 + ...
3) Nul(A) = Span (lin comb) |
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Col(A) is a subspace of the __ |
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Col(A) is a subspace of the __ |
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If Ax = b, what can you say about b |
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b is in Col(A) if a solution exists |
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Augment with a vector and see if consistent |
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If x1v1+x2v2+x3v3 + ... + xpvp = 0, and x1,x2,x3,... are non 0 |
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A single non-zero vectorv1is always __ |
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Vectors (v1,....,vp) containing the 0 vector are |
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A set of vectors{v1, . . . ,vp} in V is a basis of V if |
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V = span(vectors) vectors linearly independent |
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it has a basis of p vectors |
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To be a basis of R^n the set must |
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Basis for something like:
[image] |
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1) REF
2) Find pivot columns.
3) Basis is the columns of ORIGINAL matrix |
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1) find the parametric form of the solutions to Ax = 0 2) express solutions x as a linear combination of vectors with the free variables 3) Vectors form the basis
(basically vectors in span are in basis) |
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null space of A transpose |
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column space of A transpose |
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same as dot product betweeen 2 vectors (ex: v transpose w) |
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vectors that are unit vectors and orthogonal |
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it is orthogonal to every vector in W |
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space of all vectors that are orthogonal to the subspace W |
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Nul(A) is the orthogonal complement of |
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Col(A) is the orthogonal complement of |
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Find all vectors orthognoal to v1 and v2 |
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Find orthogonal complement to Col(v1 v2), and use nullspace (it is span(nulspace)) |
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Find all vectors orthognoal to v1 and v2 |
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Find orthogonal complement to Col(v1 v2), and use nullspace |
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T(a1)b T(a2)b T(a3)b are the matrix columns |
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Nul(A) and solutions to Ax = b |
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Let Axp = b
xp + Nul(A) will give all solutions in Nullspace. |
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The columns of A are linearly independent means ___ (3 things) |
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Ax = 0 has only the solution x = 0. Nul(A) = {0} A has n pivots |
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Vectors v1, . . . , vp containing the zero vector are linearly ____ |
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