12-240/Classnotes for Thursday October 4: Difference between revisions

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Recap
'''Recap'''

Base - what were doing today
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.
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
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
Generate - We say S generates a vector space V is span(S) = V


== Introduction to Basis ==
== 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.

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.