12-240/Classnotes for Thursday October 4: Difference between revisions
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Recap |
'''Recap''' |
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Base - what were doing today |
Base - what were doing today |
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Linear combination (lc) - We say v is a linear combination of a set S = {u1 ... un} if v = a1u1 ... anun for scalars from a field F. |
Linear combination (lc) - We say v is a linear combination of a set S = {u1 ... un} if v = a1u1 ... anun for scalars from a field F. |
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Span - span(S) is the set of all linear combination of set S |
Span - span(S) is the set of all linear combination of set S |
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Generate - We say S generates a vector space V is span(S) = V |
Generate - We say S generates a vector space V is span(S) = V |
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== Introduction to Basis == |
== Introduction to Basis == |
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'''Linear dependance''' |
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'''Definition''' A set S subsetof V is called linearly dependant if you can express the zero vector as a linear combination of distinct vectors from S, excluding the non-trivial linear combination where all of the scalars are 0. |
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Otherwise, we call S '''linearly independant.''' |
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=== Examples === |
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1. In '''R'''^3, take S = {u1 = (1,4,7), u2 = (2,5,8), u3 = (3,6,9)} |
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u1 - 2u2 + u3 = 0 |
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S is linearly dependant. |
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2. In R^n, take {e_i} = {0, 0, ... 1, 0, 0, 0} where 1 is in the ith position, and (ei) is a vector with n entries. |
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Claim: This set is linearly independent. |
Revision as of 18:34, 4 October 2012
Recap
Base - what were doing today
Linear combination (lc) - We say v is a linear combination of a set S = {u1 ... un} if v = a1u1 ... anun for scalars from a field F.
Span - span(S) is the set of all linear combination of set S
Generate - We say S generates a vector space V is span(S) = V
Introduction to Basis
Linear dependance
Definition A set S subsetof V is called linearly dependant if you can express the zero vector as a linear combination of distinct vectors from S, excluding the non-trivial linear combination where all of the scalars are 0.
Otherwise, we call S linearly independant.
Examples
1. In R^3, take S = {u1 = (1,4,7), u2 = (2,5,8), u3 = (3,6,9)}
u1 - 2u2 + u3 = 0
S is linearly dependant.
2. In R^n, take {e_i} = {0, 0, ... 1, 0, 0, 0} where 1 is in the ith position, and (ei) is a vector with n entries.
Claim: This set is linearly independent.